* [MAQAO] Info: Detected 1 Lprof instances in gmz12.benchmarkcenter.megware.com.
If this is incorrect, rerun with number-processes-per-node=X
OMP: pid 10034 tid 10034 thread 0 bound to OS proc set {0}
OMP: pid 10034 tid 10049 thread 4 bound to OS proc set {96}
OMP: pid 10034 tid 10051 thread 5 bound to OS proc set {144}
OMP: pid 10034 tid 10047 thread 3 bound to OS proc set {88}
OMP: pid 10034 tid 10045 thread 2 bound to OS proc set {32}
OMP: pid 10034 tid 10053 thread 6 bound to OS proc set {128}
OMP: pid 10034 tid 10043 thread 1 bound to OS proc set {48}
OMP: pid 10034 tid 10055 thread 7 bound to OS proc set {184}
what is a LLM? and why it’s changing the game
A Large Language Model (LLM) is a type of artificial intelligence (AI) that can process, understand, and generate human-like language. LLMs are trained on vast amounts of text data, which allows them to learn patterns, relationships, and context in language. This enables them to perform a wide range of tasks, including:
1. Answering questions: LLMs can comprehend natural language queries and provide relevant responses.
2. Generating text: LLMs can create text based on a given prompt or topic, often indistinguishable from text written by a human.
3. Translation: LLMs can translate text from one language to another, with varying degrees of accuracy.
4. Summarization: LLMs can condense long pieces of text into concise summaries.
5. Conversational dialogue: LLMs can engage in natural-sounding conversations, either as a chatbot or a conversational interface.
LLMs are changing the game in several industries:
1. **Customer service**: Chatbots powered by LLMs can provide 24/7 support, answering customer inquiries and resolving issues more efficiently than human customer support agents.
2. **Content creation**: LLMs can assist content creators, such as writers, journalists, and social media managers, by generating ideas, research, and even entire articles.
3. **Language learning**: LLMs can help language learners by providing personalized feedback, suggesting corrections, and even generating language lessons.
4. **Research**: LLMs can aid researchers by analyzing large volumes of text data, identifying patterns, and suggesting new research directions.
5. **Education**: LLMs can assist educators by generating customized learning materials, grading assignments, and even providing one-on-one tutoring.
6. **Marketing**: LLMs can help marketers by generating targeted content, analyzing customer sentiment, and optimizing marketing campaigns.
7. **Healthcare**: LLMs can assist healthcare professionals by analyzing medical literature, suggesting diagnoses, and even generating treatment plans.
LLMs are also raising important questions and concerns, such as:
1. **Job displacement**: Will LLMs replace human professionals in various industries?
2. **Bias and accuracy**: Can LLMs inherit biases from the data they're trained on, and how accurate are their responses?
3. **Accountability**: Who is responsible when LLMs provide incorrect or misleading information?
4. **Ethics**: How should LLMs be designed and
Your experiment path is /beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_0
To display your profiling results:
##########################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
##########################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_0 #
# Functions | Per-node | maqao lprof -df -dn xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_0 #
# Functions | Per-process | maqao lprof -df -dp xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_0 #
# Functions | Per-thread | maqao lprof -df -dt xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_0 #
# Loops | Cluster-wide | maqao lprof -dl xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_0 #
# Loops | Per-node | maqao lprof -dl -dn xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_0 #
# Loops | Per-process | maqao lprof -dl -dp xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_0 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_0 #
##########################################################################################################################################################################################################################
* [MAQAO] Info: Detected 1 Lprof instances in gmz12.benchmarkcenter.megware.com.
If this is incorrect, rerun with number-processes-per-node=X
OMP: pid 10115 tid 10115 thread 0 bound to OS proc set {0}
OMP: pid 10115 tid 10124 thread 2 bound to OS proc set {6}
OMP: pid 10115 tid 10234 thread 57 bound to OS proc set {187}
OMP: pid 10115 tid 10232 thread 56 bound to OS proc set {184}
OMP: pid 10115 tid 10144 thread 12 bound to OS proc set {12}
OMP: pid 10115 tid 10128 thread 4 bound to OS proc set {76}
OMP: pid 10115 tid 10242 thread 61 bound to OS proc set {143}
OMP: pid 10115 tid 10240 thread 60 bound to OS proc set {140}
OMP: pid 10115 tid 10238 thread 59 bound to OS proc set {137}
OMP: pid 10115 tid 10236 thread 58 bound to OS proc set {190}
OMP: pid 10115 tid 10122 thread 1 bound to OS proc set {3}
OMP: pid 10115 tid 10142 thread 11 bound to OS proc set {9}
OMP: pid 10115 tid 10194 thread 37 bound to OS proc set {175}
OMP: pid 10115 tid 10126 thread 3 bound to OS proc set {73}
OMP: pid 10115 tid 10146 thread 13 bound to OS proc set {15}
OMP: pid 10115 tid 10186 thread 33 bound to OS proc set {99}
OMP: pid 10115 tid 10184 thread 32 bound to OS proc set {96}
OMP: pid 10115 tid 10134 thread 7 bound to OS proc set {29}
OMP: pid 10115 tid 10188 thread 34 bound to OS proc set {102}
OMP: pid 10115 tid 10136 thread 8 bound to OS proc set {48}
OMP: pid 10115 tid 10138 thread 9 bound to OS proc set {51}
OMP: pid 10115 tid 10148 thread 14 bound to OS proc set {82}
OMP: pid 10115 tid 10190 thread 35 bound to OS proc set {169}
OMP: pid 10115 tid 10130 thread 5 bound to OS proc set {79}
OMP: pid 10115 tid 10132 thread 6 bound to OS proc set {26}
OMP: pid 10115 tid 10160 thread 20 bound to OS proc set {60}
OMP: pid 10115 tid 10198 thread 39 bound to OS proc set {125}
OMP: pid 10115 tid 10174 thread 27 bound to OS proc set {41}
OMP: pid 10115 tid 10176 thread 28 bound to OS proc set {44}
OMP: pid 10115 tid 10140 thread 10 bound to OS proc set {54}
OMP: pid 10115 tid 10158 thread 19 bound to OS proc set {57}
OMP: pid 10115 tid 10150 thread 15 bound to OS proc set {85}
OMP: pid 10115 tid 10192 thread 36 bound to OS proc set {172}
OMP: pid 10115 tid 10154 thread 17 bound to OS proc set {35}
OMP: pid 10115 tid 10216 thread 48 bound to OS proc set {128}
OMP: pid 10115 tid 10178 thread 29 bound to OS proc set {47}
OMP: pid 10115 tid 10226 thread 53 bound to OS proc set {159}
OMP: pid 10115 tid 10224 thread 52 bound to OS proc set {156}
OMP: pid 10115 tid 10246 thread 63 bound to OS proc set {165}
OMP: pid 10115 tid 10220 thread 50 bound to OS proc set {134}
OMP: pid 10115 tid 10196 thread 38 bound to OS proc set {122}
OMP: pid 10115 tid 10170 thread 25 bound to OS proc set {91}
OMP: pid 10115 tid 10172 thread 26 bound to OS proc set {94}
OMP: pid 10115 tid 10152 thread 16 bound to OS proc set {32}
OMP: pid 10115 tid 10180 thread 30 bound to OS proc set {66}
OMP: pid 10115 tid 10182 thread 31 bound to OS proc set {69}
OMP: pid 10115 tid 10228 thread 54 bound to OS proc set {114}
OMP: pid 10115 tid 10230 thread 55 bound to OS proc set {117}
OMP: pid 10115 tid 10168 thread 24 bound to OS proc set {88}
OMP: pid 10115 tid 10212 thread 46 bound to OS proc set {178}
OMP: pid 10115 tid 10200 thread 40 bound to OS proc set {144}
OMP: pid 10115 tid 10204 thread 42 bound to OS proc set {150}
OMP: pid 10115 tid 10218 thread 49 bound to OS proc set {131}
OMP: pid 10115 tid 10208 thread 44 bound to OS proc set {108}
OMP: pid 10115 tid 10206 thread 43 bound to OS proc set {105}
OMP: pid 10115 tid 10210 thread 45 bound to OS proc set {111}
OMP: pid 10115 tid 10202 thread 41 bound to OS proc set {147}
OMP: pid 10115 tid 10222 thread 51 bound to OS proc set {153}
OMP: pid 10115 tid 10156 thread 18 bound to OS proc set {38}
OMP: pid 10115 tid 10162 thread 21 bound to OS proc set {63}
OMP: pid 10115 tid 10214 thread 47 bound to OS proc set {181}
OMP: pid 10115 tid 10244 thread 62 bound to OS proc set {162}
OMP: pid 10115 tid 10164 thread 22 bound to OS proc set {18}
OMP: pid 10115 tid 10166 thread 23 bound to OS proc set {21}
what is a LLM? and why it’s changing the game
A Large Language Model (LLM) is a type of artificial intelligence (AI) that can process, understand, and generate human-like language. LLMs are trained on vast amounts of text data, which allows them to learn patterns, relationships, and context in language. This enables them to perform a wide range of tasks, including:
1. Answering questions: LLMs can comprehend natural language queries and provide relevant responses.
2. Generating text: LLMs can create text based on a given prompt or topic, often indistinguishable from text written by a human.
3. Translation: LLMs can translate text from one language to another, with varying degrees of accuracy.
4. Summarization: LLMs can condense long pieces of text into concise summaries.
5. Conversational dialogue: LLMs can engage in natural-sounding conversations, either as a chatbot or a conversational interface.
LLMs are changing the game in several industries:
1. **Customer service**: Chatbots powered by LLMs can provide 24/7 support, answering customer inquiries and resolving issues more efficiently than human customer support agents.
2. **Content creation**: LLMs can assist content creators, such as writers, journalists, and social media managers, by generating ideas, research, and even entire articles.
3. **Language learning**: LLMs can help language learners by providing personalized feedback, suggesting corrections, and even generating language lessons.
4. **Research**: LLMs can aid researchers by analyzing large volumes of text data, identifying patterns, and suggesting new research directions.
5. **Education**: LLMs can assist educators by generating customized learning materials, grading assignments, and even providing one-on-one tutoring.
6. **Marketing**: LLMs can help marketers by generating targeted content, analyzing customer sentiment, and optimizing marketing campaigns.
7. **Healthcare**: LLMs can assist healthcare professionals by analyzing medical literature, suggesting diagnoses, and even generating treatment plans.
LLMs are also raising important questions and concerns, such as:
1. **Job displacement**: Will LLMs replace human professionals in various industries?
2. **Bias and accuracy**: Can LLMs inherit biases from the data they're trained on, and how accurate are their responses?
3. **Accountability**: Who is responsible when LLMs provide incorrect or misleading information?
4. **Ethics**: How should LLMs be designed and
Your experiment path is /beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_1
To display your profiling results:
##########################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
##########################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_1 #
# Functions | Per-node | maqao lprof -df -dn xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_1 #
# Functions | Per-process | maqao lprof -df -dp xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_1 #
# Functions | Per-thread | maqao lprof -df -dt xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_1 #
# Loops | Cluster-wide | maqao lprof -dl xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_1 #
# Loops | Per-node | maqao lprof -dl -dn xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_1 #
# Loops | Per-process | maqao lprof -dl -dp xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_1 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_1 #
##########################################################################################################################################################################################################################
* [MAQAO] Info: Detected 1 Lprof instances in gmz12.benchmarkcenter.megware.com.
If this is incorrect, rerun with number-processes-per-node=X
OMP: pid 10310 tid 10310 thread 0 bound to OS proc set {0}
OMP: pid 10310 tid 10319 thread 2 bound to OS proc set {4}
OMP: pid 10310 tid 10335 thread 10 bound to OS proc set {28}
OMP: pid 10310 tid 10347 thread 16 bound to OS proc set {8}
OMP: pid 10310 tid 10333 thread 9 bound to OS proc set {26}
OMP: pid 10310 tid 10343 thread 14 bound to OS proc set {52}
OMP: pid 10310 tid 10415 thread 50 bound to OS proc set {100}
OMP: pid 10310 tid 10337 thread 11 bound to OS proc set {30}
OMP: pid 10310 tid 10331 thread 8 bound to OS proc set {24}
OMP: pid 10310 tid 10339 thread 12 bound to OS proc set {48}
OMP: pid 10310 tid 10345 thread 15 bound to OS proc set {54}
OMP: pid 10310 tid 10349 thread 17 bound to OS proc set {10}
OMP: pid 10310 tid 10325 thread 5 bound to OS proc set {74}
OMP: pid 10310 tid 10397 thread 41 bound to OS proc set {42}
OMP: pid 10310 tid 10327 thread 6 bound to OS proc set {76}
OMP: pid 10310 tid 10385 thread 35 bound to OS proc set {22}
OMP: pid 10310 tid 10323 thread 4 bound to OS proc set {72}
OMP: pid 10310 tid 10329 thread 7 bound to OS proc set {78}
OMP: pid 10310 tid 10341 thread 13 bound to OS proc set {50}
OMP: pid 10310 tid 10351 thread 18 bound to OS proc set {12}
OMP: pid 10310 tid 10411 thread 48 bound to OS proc set {96}
OMP: pid 10310 tid 10377 thread 31 bound to OS proc set {62}
OMP: pid 10310 tid 10417 thread 51 bound to OS proc set {102}
OMP: pid 10310 tid 10321 thread 3 bound to OS proc set {6}
OMP: pid 10310 tid 10317 thread 1 bound to OS proc set {2}
OMP: pid 10310 tid 10355 thread 20 bound to OS proc set {80}
OMP: pid 10310 tid 10413 thread 49 bound to OS proc set {98}
OMP: pid 10310 tid 10429 thread 57 bound to OS proc set {122}
OMP: pid 10310 tid 10427 thread 56 bound to OS proc set {120}
OMP: pid 10310 tid 10421 thread 53 bound to OS proc set {170}
OMP: pid 10310 tid 10371 thread 28 bound to OS proc set {56}
OMP: pid 10310 tid 10381 thread 33 bound to OS proc set {18}
OMP: pid 10310 tid 10419 thread 52 bound to OS proc set {168}
OMP: pid 10310 tid 10387 thread 36 bound to OS proc set {88}
OMP: pid 10310 tid 10357 thread 21 bound to OS proc set {82}
OMP: pid 10310 tid 10353 thread 19 bound to OS proc set {14}
OMP: pid 10310 tid 10361 thread 23 bound to OS proc set {86}
OMP: pid 10310 tid 10399 thread 42 bound to OS proc set {44}
OMP: pid 10310 tid 10379 thread 32 bound to OS proc set {16}
OMP: pid 10310 tid 10423 thread 54 bound to OS proc set {172}
OMP: pid 10310 tid 10395 thread 40 bound to OS proc set {40}
OMP: pid 10310 tid 10383 thread 34 bound to OS proc set {20}
OMP: pid 10310 tid 10403 thread 44 bound to OS proc set {64}
OMP: pid 10310 tid 10409 thread 47 bound to OS proc set {70}
OMP: pid 10310 tid 10407 thread 46 bound to OS proc set {68}
OMP: pid 10310 tid 10375 thread 30 bound to OS proc set {60}
OMP: pid 10310 tid 10401 thread 43 bound to OS proc set {46}
OMP: pid 10310 tid 10393 thread 39 bound to OS proc set {94}
OMP: pid 10310 tid 10369 thread 27 bound to OS proc set {38}
OMP: pid 10310 tid 10367 thread 26 bound to OS proc set {36}
OMP: pid 10310 tid 10365 thread 25 bound to OS proc set {34}
OMP: pid 10310 tid 10425 thread 55 bound to OS proc set {174}
OMP: pid 10310 tid 10405 thread 45 bound to OS proc set {66}
OMP: pid 10310 tid 10359 thread 22 bound to OS proc set {84}
OMP: pid 10310 tid 10363 thread 24 bound to OS proc set {32}
OMP: pid 10310 tid 10389 thread 37 bound to OS proc set {90}
OMP: pid 10310 tid 10391 thread 38 bound to OS proc set {92}
OMP: pid 10310 tid 10373 thread 29 bound to OS proc set {58}
OMP: pid 10310 tid 10435 thread 60 bound to OS proc set {144}
OMP: pid 10310 tid 10447 thread 66 bound to OS proc set {108}
OMP: pid 10310 tid 10437 thread 61 bound to OS proc set {146}
OMP: pid 10310 tid 10479 thread 82 bound to OS proc set {116}
OMP: pid 10310 tid 10505 thread 95 bound to OS proc set {166}
OMP: pid 10310 tid 10501 thread 93 bound to OS proc set {162}
OMP: pid 10310 tid 10499 thread 92 bound to OS proc set {160}
OMP: pid 10310 tid 10491 thread 88 bound to OS proc set {136}
OMP: pid 10310 tid 10433 thread 59 bound to OS proc set {126}
OMP: pid 10310 tid 10455 thread 70 bound to OS proc set {180}
OMP: pid 10310 tid 10443 thread 64 bound to OS proc set {104}
OMP: pid 10310 tid 10439 thread 62 bound to OS proc set {148}
OMP: pid 10310 tid 10449 thread 67 bound to OS proc set {110}
OMP: pid 10310 tid 10469 thread 77 bound to OS proc set {154}
OMP: pid 10310 tid 10467 thread 76 bound to OS proc set {152}
OMP: pid 10310 tid 10451 thread 68 bound to OS proc set {176}
OMP: pid 10310 tid 10503 thread 94 bound to OS proc set {164}
OMP: pid 10310 tid 10477 thread 81 bound to OS proc set {114}
OMP: pid 10310 tid 10495 thread 90 bound to OS proc set {140}
OMP: pid 10310 tid 10475 thread 80 bound to OS proc set {112}
OMP: pid 10310 tid 10453 thread 69 bound to OS proc set {178}
OMP: pid 10310 tid 10473 thread 79 bound to OS proc set {158}
OMP: pid 10310 tid 10493 thread 89 bound to OS proc set {138}
OMP: pid 10310 tid 10471 thread 78 bound to OS proc set {156}
OMP: pid 10310 tid 10481 thread 83 bound to OS proc set {118}
OMP: pid 10310 tid 10431 thread 58 bound to OS proc set {124}
OMP: pid 10310 tid 10497 thread 91 bound to OS proc set {142}
OMP: pid 10310 tid 10459 thread 72 bound to OS proc set {128}
OMP: pid 10310 tid 10465 thread 75 bound to OS proc set {134}
OMP: pid 10310 tid 10463 thread 74 bound to OS proc set {132}
OMP: pid 10310 tid 10441 thread 63 bound to OS proc set {150}
OMP: pid 10310 tid 10461 thread 73 bound to OS proc set {130}
OMP: pid 10310 tid 10457 thread 71 bound to OS proc set {182}
OMP: pid 10310 tid 10483 thread 84 bound to OS proc set {184}
OMP: pid 10310 tid 10445 thread 65 bound to OS proc set {106}
OMP: pid 10310 tid 10485 thread 85 bound to OS proc set {186}
OMP: pid 10310 tid 10489 thread 87 bound to OS proc set {190}
OMP: pid 10310 tid 10487 thread 86 bound to OS proc set {188}
what is a LLM? and why it’s changing the game
A Large Language Model (LLM) is a type of artificial intelligence (AI) that can process, understand, and generate human-like language. LLMs are trained on vast amounts of text data, which allows them to learn patterns, relationships, and context in language. This enables them to perform a wide range of tasks, including:
1. Answering questions: LLMs can comprehend natural language queries and provide relevant responses.
2. Generating text: LLMs can create text based on a given prompt or topic, often indistinguishable from text written by a human.
3. Translation: LLMs can translate text from one language to another, with varying degrees of accuracy.
4. Summarization: LLMs can condense long pieces of text into concise summaries.
5. Conversational dialogue: LLMs can engage in natural-sounding conversations, either as a chatbot or a conversational interface.
LLMs are changing the game in several industries:
1. **Customer service**: Chatbots powered by LLMs can provide 24/7 support, answering customer inquiries and resolving issues more efficiently than human customer support agents.
2. **Content creation**: LLMs can assist content creators, such as writers, journalists, and social media managers, by generating ideas, research, and even entire articles.
3. **Language learning**: LLMs can help language learners by providing personalized feedback, suggesting corrections, and even generating language lessons.
4. **Research**: LLMs can aid researchers by analyzing large volumes of text data, identifying patterns, and suggesting new research directions.
5. **Education**: LLMs can assist educators by generating customized learning materials, grading assignments, and even providing one-on-one tutoring.
6. **Marketing**: LLMs can help marketers by generating targeted content, analyzing customer sentiment, and optimizing marketing campaigns.
7. **Healthcare**: LLMs can assist healthcare professionals by analyzing medical literature, suggesting diagnoses, and even generating treatment plans.
LLMs are also raising important questions and concerns, such as:
1. **Job displacement**: Will LLMs replace human professionals in various industries?
2. **Bias and accuracy**: Can LLMs inherit biases from the data they're trained on, and how accurate are their responses?
3. **Accountability**: Who is responsible when LLMs provide incorrect or misleading information?
4. **Ethics**: How should LLMs be designed and
Your experiment path is /beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_2
To display your profiling results:
##########################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
##########################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_2 #
# Functions | Per-node | maqao lprof -df -dn xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_2 #
# Functions | Per-process | maqao lprof -df -dp xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_2 #
# Functions | Per-thread | maqao lprof -df -dt xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_2 #
# Loops | Cluster-wide | maqao lprof -dl xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_2 #
# Loops | Per-node | maqao lprof -dl -dn xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_2 #
# Loops | Per-process | maqao lprof -dl -dp xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_2 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_2 #
##########################################################################################################################################################################################################################
* [MAQAO] Info: Detected 1 Lprof instances in gmz12.benchmarkcenter.megware.com.
If this is incorrect, rerun with number-processes-per-node=X
OMP: pid 10570 tid 10570 thread 0 bound to OS proc set {0}
OMP: pid 10570 tid 10579 thread 2 bound to OS proc set {3}
OMP: pid 10570 tid 10585 thread 5 bound to OS proc set {199}
OMP: pid 10570 tid 10583 thread 4 bound to OS proc set {6}
OMP: pid 10570 tid 10581 thread 3 bound to OS proc set {196}
OMP: pid 10570 tid 10577 thread 1 bound to OS proc set {193}
OMP: pid 10570 tid 10603 thread 14 bound to OS proc set {29}
OMP: pid 10570 tid 10597 thread 11 bound to OS proc set {216}
OMP: pid 10570 tid 10601 thread 13 bound to OS proc set {219}
OMP: pid 10570 tid 10595 thread 10 bound to OS proc set {79}
OMP: pid 10570 tid 10611 thread 18 bound to OS proc set {51}
OMP: pid 10570 tid 10609 thread 17 bound to OS proc set {241}
OMP: pid 10570 tid 10589 thread 7 bound to OS proc set {266}
OMP: pid 10570 tid 10799 thread 112 bound to OS proc set {184}
OMP: pid 10570 tid 10805 thread 115 bound to OS proc set {380}
OMP: pid 10570 tid 10679 thread 52 bound to OS proc set {94}
OMP: pid 10570 tid 10607 thread 16 bound to OS proc set {48}
OMP: pid 10570 tid 10591 thread 8 bound to OS proc set {76}
OMP: pid 10570 tid 10599 thread 12 bound to OS proc set {26}
OMP: pid 10570 tid 10593 thread 9 bound to OS proc set {269}
OMP: pid 10570 tid 10613 thread 19 bound to OS proc set {244}
OMP: pid 10570 tid 10691 thread 58 bound to OS proc set {47}
OMP: pid 10570 tid 10687 thread 56 bound to OS proc set {44}
OMP: pid 10570 tid 10745 thread 85 bound to OS proc set {343}
OMP: pid 10570 tid 10695 thread 60 bound to OS proc set {66}
OMP: pid 10570 tid 10587 thread 6 bound to OS proc set {73}
OMP: pid 10570 tid 10631 thread 28 bound to OS proc set {82}
OMP: pid 10570 tid 10683 thread 54 bound to OS proc set {41}
OMP: pid 10570 tid 10783 thread 104 bound to OS proc set {156}
OMP: pid 10570 tid 10675 thread 50 bound to OS proc set {91}
OMP: pid 10570 tid 10699 thread 62 bound to OS proc set {69}
OMP: pid 10570 tid 10705 thread 65 bound to OS proc set {289}
OMP: pid 10570 tid 10605 thread 15 bound to OS proc set {222}
OMP: pid 10570 tid 10671 thread 48 bound to OS proc set {88}
OMP: pid 10570 tid 10709 thread 67 bound to OS proc set {292}
OMP: pid 10570 tid 10619 thread 22 bound to OS proc set {9}
OMP: pid 10570 tid 10803 thread 114 bound to OS proc set {187}
OMP: pid 10570 tid 10775 thread 100 bound to OS proc set {134}
OMP: pid 10570 tid 10615 thread 20 bound to OS proc set {54}
OMP: pid 10570 tid 10729 thread 77 bound to OS proc set {315}
OMP: pid 10570 tid 10813 thread 119 bound to OS proc set {330}
OMP: pid 10570 tid 10811 thread 118 bound to OS proc set {137}
OMP: pid 10570 tid 10649 thread 37 bound to OS proc set {231}
OMP: pid 10570 tid 10823 thread 124 bound to OS proc set {162}
OMP: pid 10570 tid 10779 thread 102 bound to OS proc set {153}
OMP: pid 10570 tid 10635 thread 30 bound to OS proc set {85}
OMP: pid 10570 tid 10737 thread 81 bound to OS proc set {337}
OMP: pid 10570 tid 10713 thread 69 bound to OS proc set {295}
OMP: pid 10570 tid 10809 thread 117 bound to OS proc set {383}
OMP: pid 10570 tid 10801 thread 113 bound to OS proc set {377}
OMP: pid 10570 tid 10791 thread 108 bound to OS proc set {114}
OMP: pid 10570 tid 10827 thread 126 bound to OS proc set {165}
OMP: pid 10570 tid 10797 thread 111 bound to OS proc set {310}
OMP: pid 10570 tid 10807 thread 116 bound to OS proc set {190}
OMP: pid 10570 tid 10795 thread 110 bound to OS proc set {117}
OMP: pid 10570 tid 10647 thread 36 bound to OS proc set {38}
OMP: pid 10570 tid 10641 thread 33 bound to OS proc set {225}
OMP: pid 10570 tid 10817 thread 121 bound to OS proc set {333}
OMP: pid 10570 tid 10743 thread 84 bound to OS proc set {150}
OMP: pid 10570 tid 10689 thread 57 bound to OS proc set {237}
OMP: pid 10570 tid 10829 thread 127 bound to OS proc set {358}
OMP: pid 10570 tid 10623 thread 24 bound to OS proc set {12}
OMP: pid 10570 tid 10781 thread 103 bound to OS proc set {346}
OMP: pid 10570 tid 10703 thread 64 bound to OS proc set {96}
OMP: pid 10570 tid 10625 thread 25 bound to OS proc set {205}
OMP: pid 10570 tid 10751 thread 88 bound to OS proc set {108}
OMP: pid 10570 tid 10819 thread 122 bound to OS proc set {143}
OMP: pid 10570 tid 10767 thread 96 bound to OS proc set {128}
OMP: pid 10570 tid 10677 thread 51 bound to OS proc set {284}
OMP: pid 10570 tid 10637 thread 31 bound to OS proc set {278}
OMP: pid 10570 tid 10755 thread 90 bound to OS proc set {111}
OMP: pid 10570 tid 10753 thread 89 bound to OS proc set {301}
OMP: pid 10570 tid 10653 thread 39 bound to OS proc set {250}
OMP: pid 10570 tid 10769 thread 97 bound to OS proc set {321}
OMP: pid 10570 tid 10617 thread 21 bound to OS proc set {247}
OMP: pid 10570 tid 10733 thread 79 bound to OS proc set {318}
OMP: pid 10570 tid 10777 thread 101 bound to OS proc set {327}
OMP: pid 10570 tid 10627 thread 26 bound to OS proc set {15}
OMP: pid 10570 tid 10657 thread 41 bound to OS proc set {253}
OMP: pid 10570 tid 10735 thread 80 bound to OS proc set {144}
OMP: pid 10570 tid 10727 thread 76 bound to OS proc set {122}
OMP: pid 10570 tid 10701 thread 63 bound to OS proc set {262}
OMP: pid 10570 tid 10731 thread 78 bound to OS proc set {125}
OMP: pid 10570 tid 10771 thread 98 bound to OS proc set {131}
OMP: pid 10570 tid 10707 thread 66 bound to OS proc set {99}
OMP: pid 10570 tid 10681 thread 53 bound to OS proc set {287}
OMP: pid 10570 tid 10629 thread 27 bound to OS proc set {272}
OMP: pid 10570 tid 10785 thread 105 bound to OS proc set {349}
OMP: pid 10570 tid 10725 thread 75 bound to OS proc set {312}
OMP: pid 10570 tid 10765 thread 95 bound to OS proc set {374}
OMP: pid 10570 tid 10793 thread 109 bound to OS proc set {307}
OMP: pid 10570 tid 10697 thread 61 bound to OS proc set {259}
OMP: pid 10570 tid 10787 thread 106 bound to OS proc set {159}
OMP: pid 10570 tid 10763 thread 94 bound to OS proc set {181}
OMP: pid 10570 tid 10651 thread 38 bound to OS proc set {57}
OMP: pid 10570 tid 10685 thread 55 bound to OS proc set {234}
OMP: pid 10570 tid 10739 thread 82 bound to OS proc set {147}
OMP: pid 10570 tid 10673 thread 49 bound to OS proc set {281}
OMP: pid 10570 tid 10717 thread 71 bound to OS proc set {362}
OMP: pid 10570 tid 10659 thread 42 bound to OS proc set {63}
OMP: pid 10570 tid 10773 thread 99 bound to OS proc set {324}
OMP: pid 10570 tid 10759 thread 92 bound to OS proc set {178}
OMP: pid 10570 tid 10825 thread 125 bound to OS proc set {355}
OMP: pid 10570 tid 10761 thread 93 bound to OS proc set {371}
OMP: pid 10570 tid 10645 thread 35 bound to OS proc set {228}
OMP: pid 10570 tid 10757 thread 91 bound to OS proc set {368}
OMP: pid 10570 tid 10815 thread 120 bound to OS proc set {140}
OMP: pid 10570 tid 10639 thread 32 bound to OS proc set {32}
OMP: pid 10570 tid 10633 thread 29 bound to OS proc set {275}
OMP: pid 10570 tid 10821 thread 123 bound to OS proc set {352}
OMP: pid 10570 tid 10693 thread 59 bound to OS proc set {256}
OMP: pid 10570 tid 10621 thread 23 bound to OS proc set {202}
OMP: pid 10570 tid 10789 thread 107 bound to OS proc set {304}
OMP: pid 10570 tid 10741 thread 83 bound to OS proc set {340}
OMP: pid 10570 tid 10749 thread 87 bound to OS proc set {298}
OMP: pid 10570 tid 10719 thread 72 bound to OS proc set {172}
OMP: pid 10570 tid 10711 thread 68 bound to OS proc set {102}
OMP: pid 10570 tid 10715 thread 70 bound to OS proc set {169}
OMP: pid 10570 tid 10663 thread 44 bound to OS proc set {18}
OMP: pid 10570 tid 10667 thread 46 bound to OS proc set {21}
OMP: pid 10570 tid 10723 thread 74 bound to OS proc set {175}
OMP: pid 10570 tid 10655 thread 40 bound to OS proc set {60}
OMP: pid 10570 tid 10747 thread 86 bound to OS proc set {105}
OMP: pid 10570 tid 10669 thread 47 bound to OS proc set {214}
OMP: pid 10570 tid 10643 thread 34 bound to OS proc set {35}
OMP: pid 10570 tid 10721 thread 73 bound to OS proc set {365}
OMP: pid 10570 tid 10665 thread 45 bound to OS proc set {211}
OMP: pid 10570 tid 10661 thread 43 bound to OS proc set {208}
what is a LLM? and why it’s changing the game
A Large Language Model (LLM) is a type of artificial intelligence (AI) that can process, understand, and generate human-like language. LLMs are trained on vast amounts of text data, which allows them to learn patterns, relationships, and context in language. This enables them to perform a wide range of tasks, including:
1. Answering questions: LLMs can comprehend natural language queries and provide relevant responses.
2. Generating text: LLMs can create text based on a given prompt or topic, often indistinguishable from text written by a human.
3. Translation: LLMs can translate text from one language to another, with varying degrees of accuracy.
4. Summarization: LLMs can condense long pieces of text into concise summaries.
5. Conversational dialogue: LLMs can engage in natural-sounding conversations, either as a chatbot or a conversational interface.
LLMs are changing the game in several industries:
1. **Customer service**: Chatbots powered by LLMs can provide 24/7 support, answering customer inquiries and resolving issues more efficiently than human customer support agents.
2. **Content creation**: LLMs can assist content creators, such as writers, journalists, and social media managers, by generating ideas, research, and even entire articles.
3. **Language learning**: LLMs can help language learners by providing personalized feedback, suggesting corrections, and even generating language lessons.
4. **Research**: LLMs can aid researchers by analyzing large volumes of text data, identifying patterns, and suggesting new research directions.
5. **Education**: LLMs can assist educators by generating customized learning materials, grading assignments, and even providing one-on-one tutoring.
6. **Marketing**: LLMs can help marketers by generating targeted content, analyzing customer sentiment, and optimizing marketing campaigns.
7. **Healthcare**: LLMs can assist healthcare professionals by analyzing medical literature, suggesting diagnoses, and even generating treatment plans.
LLMs are also raising important questions and concerns, such as:
1. **Job displacement**: Will LLMs replace human professionals in various industries?
2. **Bias and accuracy**: Can LLMs inherit biases from the data they're trained on, and how accurate are their responses?
3. **Accountability**: Who is responsible when LLMs provide incorrect or misleading information?
4. **Ethics**: How should LLMs be designed and
Your experiment path is /beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_3
To display your profiling results:
##########################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
##########################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_3 #
# Functions | Per-node | maqao lprof -df -dn xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_3 #
# Functions | Per-process | maqao lprof -df -dp xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_3 #
# Functions | Per-thread | maqao lprof -df -dt xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_3 #
# Loops | Cluster-wide | maqao lprof -dl xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_3 #
# Loops | Per-node | maqao lprof -dl -dn xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_3 #
# Loops | Per-process | maqao lprof -dl -dp xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_3 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_3 #
##########################################################################################################################################################################################################################
* [MAQAO] Info: Detected 1 Lprof instances in gmz12.benchmarkcenter.megware.com.
If this is incorrect, rerun with number-processes-per-node=X
OMP: pid 10889 tid 10889 thread 0 bound to OS proc set {0}
OMP: pid 10889 tid 10900 thread 2 bound to OS proc set {2}
OMP: pid 10889 tid 10906 thread 5 bound to OS proc set {6}
OMP: pid 10889 tid 10908 thread 6 bound to OS proc set {7}
OMP: pid 10889 tid 10904 thread 4 bound to OS proc set {196}
OMP: pid 10889 tid 10994 thread 49 bound to OS proc set {250}
OMP: pid 10889 tid 10996 thread 50 bound to OS proc set {60}
OMP: pid 10889 tid 10998 thread 51 bound to OS proc set {61}
OMP: pid 10889 tid 11002 thread 53 bound to OS proc set {255}
OMP: pid 10889 tid 11000 thread 52 bound to OS proc set {254}
OMP: pid 10889 tid 10992 thread 48 bound to OS proc set {249}
OMP: pid 10889 tid 10902 thread 3 bound to OS proc set {195}
OMP: pid 10889 tid 10922 thread 13 bound to OS proc set {271}
OMP: pid 10889 tid 10898 thread 1 bound to OS proc set {1}
OMP: pid 10889 tid 10924 thread 14 bound to OS proc set {216}
OMP: pid 10889 tid 10928 thread 16 bound to OS proc set {27}
OMP: pid 10889 tid 10920 thread 12 bound to OS proc set {78}
OMP: pid 10889 tid 10950 thread 27 bound to OS proc set {8}
OMP: pid 10889 tid 10910 thread 7 bound to OS proc set {72}
OMP: pid 10889 tid 10918 thread 11 bound to OS proc set {77}
OMP: pid 10889 tid 10926 thread 15 bound to OS proc set {26}
OMP: pid 10889 tid 10914 thread 9 bound to OS proc set {266}
OMP: pid 10889 tid 11024 thread 64 bound to OS proc set {93}
OMP: pid 10889 tid 10952 thread 28 bound to OS proc set {201}
OMP: pid 10889 tid 10932 thread 18 bound to OS proc set {221}
OMP: pid 10889 tid 10916 thread 10 bound to OS proc set {76}
OMP: pid 10889 tid 10930 thread 17 bound to OS proc set {28}
OMP: pid 10889 tid 11018 thread 61 bound to OS proc set {89}
OMP: pid 10889 tid 10912 thread 8 bound to OS proc set {265}
OMP: pid 10889 tid 10934 thread 19 bound to OS proc set {222}
OMP: pid 10889 tid 11016 thread 60 bound to OS proc set {88}
OMP: pid 10889 tid 10962 thread 33 bound to OS proc set {207}
OMP: pid 10889 tid 11022 thread 63 bound to OS proc set {283}
OMP: pid 10889 tid 11006 thread 55 bound to OS proc set {18}
OMP: pid 10889 tid 11004 thread 54 bound to OS proc set {208}
OMP: pid 10889 tid 10958 thread 31 bound to OS proc set {13}
OMP: pid 10889 tid 11020 thread 62 bound to OS proc set {282}
OMP: pid 10889 tid 11012 thread 58 bound to OS proc set {213}
OMP: pid 10889 tid 11028 thread 66 bound to OS proc set {95}
OMP: pid 10889 tid 10990 thread 47 bound to OS proc set {248}
OMP: pid 10889 tid 10954 thread 29 bound to OS proc set {202}
OMP: pid 10889 tid 10956 thread 30 bound to OS proc set {12}
OMP: pid 10889 tid 10960 thread 32 bound to OS proc set {206}
OMP: pid 10889 tid 11014 thread 59 bound to OS proc set {214}
OMP: pid 10889 tid 10976 thread 40 bound to OS proc set {32}
OMP: pid 10889 tid 10978 thread 41 bound to OS proc set {33}
OMP: pid 10889 tid 10980 thread 42 bound to OS proc set {226}
OMP: pid 10889 tid 11008 thread 56 bound to OS proc set {19}
OMP: pid 10889 tid 10982 thread 43 bound to OS proc set {227}
OMP: pid 10889 tid 10946 thread 25 bound to OS proc set {54}
OMP: pid 10889 tid 10948 thread 26 bound to OS proc set {55}
OMP: pid 10889 tid 11010 thread 57 bound to OS proc set {212}
OMP: pid 10889 tid 11026 thread 65 bound to OS proc set {94}
OMP: pid 10889 tid 11038 thread 71 bound to OS proc set {45}
OMP: pid 10889 tid 11030 thread 67 bound to OS proc set {232}
OMP: pid 10889 tid 11032 thread 68 bound to OS proc set {233}
OMP: pid 10889 tid 10984 thread 44 bound to OS proc set {228}
OMP: pid 10889 tid 11034 thread 69 bound to OS proc set {43}
OMP: pid 10889 tid 10944 thread 24 bound to OS proc set {244}
OMP: pid 10889 tid 10940 thread 22 bound to OS proc set {50}
OMP: pid 10889 tid 10938 thread 21 bound to OS proc set {49}
OMP: pid 10889 tid 10942 thread 23 bound to OS proc set {243}
OMP: pid 10889 tid 10988 thread 46 bound to OS proc set {39}
OMP: pid 10889 tid 10986 thread 45 bound to OS proc set {38}
OMP: pid 10889 tid 10936 thread 20 bound to OS proc set {48}
OMP: pid 10889 tid 10964 thread 34 bound to OS proc set {272}
OMP: pid 10889 tid 10966 thread 35 bound to OS proc set {82}
OMP: pid 10889 tid 11036 thread 70 bound to OS proc set {44}
OMP: pid 10889 tid 11042 thread 73 bound to OS proc set {239}
OMP: pid 10889 tid 11040 thread 72 bound to OS proc set {238}
OMP: pid 10889 tid 10968 thread 36 bound to OS proc set {83}
OMP: pid 10889 tid 10972 thread 38 bound to OS proc set {277}
OMP: pid 10889 tid 10974 thread 39 bound to OS proc set {278}
OMP: pid 10889 tid 10970 thread 37 bound to OS proc set {276}
OMP: pid 10889 tid 11208 thread 156 bound to OS proc set {355}
OMP: pid 10889 tid 11136 thread 120 bound to OS proc set {128}
OMP: pid 10889 tid 11124 thread 114 bound to OS proc set {177}
OMP: pid 10889 tid 11152 thread 128 bound to OS proc set {154}
OMP: pid 10889 tid 11196 thread 150 bound to OS proc set {140}
OMP: pid 10889 tid 11206 thread 155 bound to OS proc set {162}
OMP: pid 10889 tid 11200 thread 152 bound to OS proc set {334}
OMP: pid 10889 tid 11140 thread 122 bound to OS proc set {322}
OMP: pid 10889 tid 11194 thread 149 bound to OS proc set {139}
OMP: pid 10889 tid 11138 thread 121 bound to OS proc set {321}
OMP: pid 10889 tid 11198 thread 151 bound to OS proc set {333}
OMP: pid 10889 tid 11202 thread 153 bound to OS proc set {160}
OMP: pid 10889 tid 11174 thread 139 bound to OS proc set {119}
OMP: pid 10889 tid 11172 thread 138 bound to OS proc set {118}
OMP: pid 10889 tid 11120 thread 112 bound to OS proc set {302}
OMP: pid 10889 tid 11184 thread 144 bound to OS proc set {189}
OMP: pid 10889 tid 11188 thread 146 bound to OS proc set {383}
OMP: pid 10889 tid 11168 thread 136 bound to OS proc set {307}
OMP: pid 10889 tid 11214 thread 159 bound to OS proc set {167}
OMP: pid 10889 tid 11190 thread 147 bound to OS proc set {328}
OMP: pid 10889 tid 11158 thread 131 bound to OS proc set {349}
OMP: pid 10889 tid 11210 thread 157 bound to OS proc set {356}
OMP: pid 10889 tid 11212 thread 158 bound to OS proc set {166}
OMP: pid 10889 tid 11204 thread 154 bound to OS proc set {161}
OMP: pid 10889 tid 11132 thread 118 bound to OS proc set {373}
OMP: pid 10889 tid 11126 thread 115 bound to OS proc set {178}
OMP: pid 10889 tid 11128 thread 116 bound to OS proc set {371}
OMP: pid 10889 tid 11130 thread 117 bound to OS proc set {372}
OMP: pid 10889 tid 11186 thread 145 bound to OS proc set {190}
OMP: pid 10889 tid 11150 thread 127 bound to OS proc set {344}
OMP: pid 10889 tid 11192 thread 148 bound to OS proc set {138}
OMP: pid 10889 tid 11142 thread 123 bound to OS proc set {323}
OMP: pid 10889 tid 11170 thread 137 bound to OS proc set {308}
OMP: pid 10889 tid 11134 thread 119 bound to OS proc set {183}
OMP: pid 10889 tid 11144 thread 124 bound to OS proc set {133}
OMP: pid 10889 tid 11156 thread 130 bound to OS proc set {156}
OMP: pid 10889 tid 11148 thread 126 bound to OS proc set {327}
OMP: pid 10889 tid 11160 thread 132 bound to OS proc set {350}
OMP: pid 10889 tid 11162 thread 133 bound to OS proc set {112}
OMP: pid 10889 tid 11146 thread 125 bound to OS proc set {134}
OMP: pid 10889 tid 11154 thread 129 bound to OS proc set {155}
OMP: pid 10889 tid 11164 thread 134 bound to OS proc set {113}
OMP: pid 10889 tid 11122 thread 113 bound to OS proc set {303}
OMP: pid 10889 tid 11166 thread 135 bound to OS proc set {114}
OMP: pid 10889 tid 11178 thread 141 bound to OS proc set {377}
OMP: pid 10889 tid 11176 thread 140 bound to OS proc set {184}
OMP: pid 10889 tid 11182 thread 143 bound to OS proc set {188}
OMP: pid 10889 tid 11180 thread 142 bound to OS proc set {378}
OMP: pid 10889 tid 11046 thread 75 bound to OS proc set {66}
OMP: pid 10889 tid 11090 thread 97 bound to OS proc set {316}
OMP: pid 10889 tid 11088 thread 96 bound to OS proc set {315}
OMP: pid 10889 tid 11094 thread 99 bound to OS proc set {127}
OMP: pid 10889 tid 11098 thread 101 bound to OS proc set {337}
OMP: pid 10889 tid 11116 thread 110 bound to OS proc set {108}
OMP: pid 10889 tid 11074 thread 89 bound to OS proc set {171}
OMP: pid 10889 tid 11048 thread 76 bound to OS proc set {67}
OMP: pid 10889 tid 11044 thread 74 bound to OS proc set {65}
OMP: pid 10889 tid 11080 thread 92 bound to OS proc set {366}
OMP: pid 10889 tid 11054 thread 79 bound to OS proc set {71}
OMP: pid 10889 tid 11114 thread 109 bound to OS proc set {107}
OMP: pid 10889 tid 11086 thread 95 bound to OS proc set {122}
OMP: pid 10889 tid 11060 thread 82 bound to OS proc set {290}
OMP: pid 10889 tid 11092 thread 98 bound to OS proc set {317}
OMP: pid 10889 tid 11112 thread 108 bound to OS proc set {297}
OMP: pid 10889 tid 11096 thread 100 bound to OS proc set {144}
OMP: pid 10889 tid 11076 thread 90 bound to OS proc set {172}
OMP: pid 10889 tid 11118 thread 111 bound to OS proc set {301}
OMP: pid 10889 tid 11068 thread 86 bound to OS proc set {103}
OMP: pid 10889 tid 11064 thread 84 bound to OS proc set {101}
OMP: pid 10889 tid 11062 thread 83 bound to OS proc set {291}
OMP: pid 10889 tid 11052 thread 78 bound to OS proc set {261}
OMP: pid 10889 tid 11084 thread 94 bound to OS proc set {121}
OMP: pid 10889 tid 11078 thread 91 bound to OS proc set {173}
OMP: pid 10889 tid 11082 thread 93 bound to OS proc set {367}
OMP: pid 10889 tid 11070 thread 87 bound to OS proc set {360}
OMP: pid 10889 tid 11066 thread 85 bound to OS proc set {102}
OMP: pid 10889 tid 11058 thread 81 bound to OS proc set {97}
OMP: pid 10889 tid 11072 thread 88 bound to OS proc set {361}
OMP: pid 10889 tid 11056 thread 80 bound to OS proc set {96}
OMP: pid 10889 tid 11050 thread 77 bound to OS proc set {260}
OMP: pid 10889 tid 11100 thread 102 bound to OS proc set {338}
OMP: pid 10889 tid 11110 thread 107 bound to OS proc set {296}
OMP: pid 10889 tid 11106 thread 105 bound to OS proc set {150}
OMP: pid 10889 tid 11102 thread 103 bound to OS proc set {339}
OMP: pid 10889 tid 11104 thread 104 bound to OS proc set {149}
OMP: pid 10889 tid 11108 thread 106 bound to OS proc set {343}
what is a LLM? and why it’s changing the game
A Large Language Model (LLM) is a type of artificial intelligence (AI) that can process, understand, and generate human-like language. LLMs are trained on vast amounts of text data, which allows them to learn patterns, relationships, and context in language. This enables them to perform a wide range of tasks, including:
1. Answering questions: LLMs can comprehend natural language queries and provide relevant responses.
2. Generating text: LLMs can create text based on a given prompt or topic, often indistinguishable from text written by a human.
3. Translation: LLMs can translate text from one language to another, with varying degrees of accuracy.
4. Summarization: LLMs can condense long pieces of text into concise summaries.
5. Conversational dialogue: LLMs can engage in natural-sounding conversations, either as a chatbot or a conversational interface.
LLMs are changing the game in several industries:
1. **Customer service**: Chatbots powered by LLMs can provide 24/7 support, answering customer inquiries and resolving issues more efficiently than human customer support agents.
2. **Content creation**: LLMs can assist content creators, such as writers, journalists, and social media managers, by generating ideas, research, and even entire articles.
3. **Language learning**: LLMs can help language learners by providing personalized feedback, suggesting corrections, and even generating language lessons.
4. **Research**: LLMs can aid researchers by analyzing large volumes of text data, identifying patterns, and suggesting new research directions.
5. **Education**: LLMs can assist educators by generating customized learning materials, grading assignments, and even providing one-on-one tutoring.
6. **Marketing**: LLMs can help marketers by generating targeted content, analyzing customer sentiment, and optimizing marketing campaigns.
7. **Healthcare**: LLMs can assist healthcare professionals by analyzing medical literature, suggesting diagnoses, and even generating treatment plans.
LLMs are also raising important questions and concerns, such as:
1. **Job displacement**: Will LLMs replace human professionals in various industries?
2. **Bias and accuracy**: Can LLMs inherit biases from the data they're trained on, and how accurate are their responses?
3. **Accountability**: Who is responsible when LLMs provide incorrect or misleading information?
4. **Ethics**: How should LLMs be designed and
Your experiment path is /beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_4
To display your profiling results:
##########################################################################################################################################################################################################################
# LEVEL | REPORT | COMMAND #
##########################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_4 #
# Functions | Per-node | maqao lprof -df -dn xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_4 #
# Functions | Per-process | maqao lprof -df -dp xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_4 #
# Functions | Per-thread | maqao lprof -df -dt xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_4 #
# Loops | Cluster-wide | maqao lprof -dl xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_4 #
# Loops | Per-node | maqao lprof -dl -dn xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_4 #
# Loops | Per-process | maqao lprof -dl -dp xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_4 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_4 #
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* [MAQAO] Info: Detected 1 Lprof instances in gmz12.benchmarkcenter.megware.com.
If this is incorrect, rerun with number-processes-per-node=X
OMP: pid 11276 tid 11540 thread 129 bound to OS proc set {105}
OMP: pid 11276 tid 11534 thread 126 bound to OS proc set {150}
OMP: pid 11276 tid 11536 thread 127 bound to OS proc set {151}
OMP: pid 11276 tid 11482 thread 100 bound to OS proc set {100}
OMP: pid 11276 tid 11474 thread 96 bound to OS proc set {96}
OMP: pid 11276 tid 11476 thread 97 bound to OS proc set {97}
OMP: pid 11276 tid 11478 thread 98 bound to OS proc set {98}
OMP: pid 11276 tid 11650 thread 184 bound to OS proc set {160}
OMP: pid 11276 tid 11502 thread 110 bound to OS proc set {174}
OMP: pid 11276 tid 11538 thread 128 bound to OS proc set {104}
OMP: pid 11276 tid 11552 thread 135 bound to OS proc set {111}
OMP: pid 11276 tid 11480 thread 99 bound to OS proc set {99}
OMP: pid 11276 tid 11548 thread 133 bound to OS proc set {109}
OMP: pid 11276 tid 11660 thread 189 bound to OS proc set {165}
OMP: pid 11276 tid 11276 thread 0 bound to OS proc set {0}
OMP: pid 11276 tid 11546 thread 132 bound to OS proc set {108}
OMP: pid 11276 tid 11542 thread 130 bound to OS proc set {106}
OMP: pid 11276 tid 11544 thread 131 bound to OS proc set {107}
OMP: pid 11276 tid 11602 thread 160 bound to OS proc set {112}
OMP: pid 11276 tid 11530 thread 124 bound to OS proc set {148}
OMP: pid 11276 tid 11490 thread 104 bound to OS proc set {168}
OMP: pid 11276 tid 11608 thread 163 bound to OS proc set {115}
OMP: pid 11276 tid 11532 thread 125 bound to OS proc set {149}
OMP: pid 11276 tid 11504 thread 111 bound to OS proc set {175}
OMP: pid 11276 tid 11492 thread 105 bound to OS proc set {169}
OMP: pid 11276 tid 11640 thread 179 bound to OS proc set {139}
OMP: pid 11276 tid 11496 thread 107 bound to OS proc set {171}
OMP: pid 11276 tid 11484 thread 101 bound to OS proc set {101}
OMP: pid 11276 tid 11558 thread 138 bound to OS proc set {178}
OMP: pid 11276 tid 11556 thread 137 bound to OS proc set {177}
OMP: pid 11276 tid 11560 thread 139 bound to OS proc set {179}
OMP: pid 11276 tid 11554 thread 136 bound to OS proc set {176}
OMP: pid 11276 tid 11562 thread 140 bound to OS proc set {180}
OMP: pid 11276 tid 11510 thread 114 bound to OS proc set {122}
OMP: pid 11276 tid 11520 thread 119 bound to OS proc set {127}
OMP: pid 11276 tid 11632 thread 175 bound to OS proc set {191}
OMP: pid 11276 tid 11618 thread 168 bound to OS proc set {184}
OMP: pid 11276 tid 11604 thread 161 bound to OS proc set {113}
OMP: pid 11276 tid 11486 thread 102 bound to OS proc set {102}
OMP: pid 11276 tid 11614 thread 166 bound to OS proc set {118}
OMP: pid 11276 tid 11656 thread 187 bound to OS proc set {163}
OMP: pid 11276 tid 11506 thread 112 bound to OS proc set {120}
OMP: pid 11276 tid 11498 thread 108 bound to OS proc set {172}
OMP: pid 11276 tid 11658 thread 188 bound to OS proc set {164}
OMP: pid 11276 tid 11652 thread 185 bound to OS proc set {161}
OMP: pid 11276 tid 11606 thread 162 bound to OS proc set {114}
OMP: pid 11276 tid 11654 thread 186 bound to OS proc set {162}
OMP: pid 11276 tid 11634 thread 176 bound to OS proc set {136}
OMP: pid 11276 tid 11564 thread 141 bound to OS proc set {181}
OMP: pid 11276 tid 11512 thread 115 bound to OS proc set {123}
OMP: pid 11276 tid 11662 thread 190 bound to OS proc set {166}
OMP: pid 11276 tid 11664 thread 191 bound to OS proc set {167}
OMP: pid 11276 tid 11514 thread 116 bound to OS proc set {124}
OMP: pid 11276 tid 11646 thread 182 bound to OS proc set {142}
OMP: pid 11276 tid 11628 thread 173 bound to OS proc set {189}
OMP: pid 11276 tid 11500 thread 109 bound to OS proc set {173}
OMP: pid 11276 tid 11494 thread 106 bound to OS proc set {170}
OMP: pid 11276 tid 11612 thread 165 bound to OS proc set {117}
OMP: pid 11276 tid 11516 thread 117 bound to OS proc set {125}
OMP: pid 11276 tid 11468 thread 93 bound to OS proc set {69}
OMP: pid 11276 tid 11466 thread 92 bound to OS proc set {68}
OMP: pid 11276 tid 11518 thread 118 bound to OS proc set {126}
OMP: pid 11276 tid 11626 thread 172 bound to OS proc set {188}
OMP: pid 11276 tid 11410 thread 64 bound to OS proc set {16}
OMP: pid 11276 tid 11616 thread 167 bound to OS proc set {119}
OMP: pid 11276 tid 11630 thread 174 bound to OS proc set {190}
OMP: pid 11276 tid 11522 thread 120 bound to OS proc set {144}
OMP: pid 11276 tid 11456 thread 87 bound to OS proc set {47}
OMP: pid 11276 tid 11648 thread 183 bound to OS proc set {143}
OMP: pid 11276 tid 11412 thread 65 bound to OS proc set {17}
OMP: pid 11276 tid 11416 thread 67 bound to OS proc set {19}
OMP: pid 11276 tid 11440 thread 79 bound to OS proc set {95}
OMP: pid 11276 tid 11524 thread 121 bound to OS proc set {145}
OMP: pid 11276 tid 11610 thread 164 bound to OS proc set {116}
OMP: pid 11276 tid 11622 thread 170 bound to OS proc set {186}
OMP: pid 11276 tid 11620 thread 169 bound to OS proc set {185}
OMP: pid 11276 tid 11528 thread 123 bound to OS proc set {147}
OMP: pid 11276 tid 11566 thread 142 bound to OS proc set {182}
OMP: pid 11276 tid 11644 thread 181 bound to OS proc set {141}
OMP: pid 11276 tid 11470 thread 94 bound to OS proc set {70}
OMP: pid 11276 tid 11642 thread 180 bound to OS proc set {140}
OMP: pid 11276 tid 11488 thread 103 bound to OS proc set {103}
OMP: pid 11276 tid 11638 thread 178 bound to OS proc set {138}
OMP: pid 11276 tid 11624 thread 171 bound to OS proc set {187}
OMP: pid 11276 tid 11424 thread 71 bound to OS proc set {23}
OMP: pid 11276 tid 11472 thread 95 bound to OS proc set {71}
OMP: pid 11276 tid 11400 thread 59 bound to OS proc set {59}
OMP: pid 11276 tid 11394 thread 56 bound to OS proc set {56}
OMP: pid 11276 tid 11636 thread 177 bound to OS proc set {137}
OMP: pid 11276 tid 11550 thread 134 bound to OS proc set {110}
OMP: pid 11276 tid 11434 thread 76 bound to OS proc set {92}
OMP: pid 11276 tid 11452 thread 85 bound to OS proc set {45}
OMP: pid 11276 tid 11390 thread 54 bound to OS proc set {38}
OMP: pid 11276 tid 11398 thread 58 bound to OS proc set {58}
OMP: pid 11276 tid 11378 thread 48 bound to OS proc set {32}
OMP: pid 11276 tid 11384 thread 51 bound to OS proc set {35}
OMP: pid 11276 tid 11446 thread 82 bound to OS proc set {42}
OMP: pid 11276 tid 11414 thread 66 bound to OS proc set {18}
OMP: pid 11276 tid 11380 thread 49 bound to OS proc set {33}
OMP: pid 11276 tid 11580 thread 149 bound to OS proc set {133}
OMP: pid 11276 tid 11408 thread 63 bound to OS proc set {63}
OMP: pid 11276 tid 11448 thread 83 bound to OS proc set {43}
OMP: pid 11276 tid 11388 thread 53 bound to OS proc set {37}
OMP: pid 11276 tid 11382 thread 50 bound to OS proc set {34}
OMP: pid 11276 tid 11386 thread 52 bound to OS proc set {36}
OMP: pid 11276 tid 11432 thread 75 bound to OS proc set {91}
OMP: pid 11276 tid 11508 thread 113 bound to OS proc set {121}
OMP: pid 11276 tid 11396 thread 57 bound to OS proc set {57}
OMP: pid 11276 tid 11444 thread 81 bound to OS proc set {41}
OMP: pid 11276 tid 11442 thread 80 bound to OS proc set {40}
OMP: pid 11276 tid 11450 thread 84 bound to OS proc set {44}
OMP: pid 11276 tid 11574 thread 146 bound to OS proc set {130}
OMP: pid 11276 tid 11570 thread 144 bound to OS proc set {128}
OMP: pid 11276 tid 11402 thread 60 bound to OS proc set {60}
OMP: pid 11276 tid 11406 thread 62 bound to OS proc set {62}
OMP: pid 11276 tid 11392 thread 55 bound to OS proc set {39}
OMP: pid 11276 tid 11578 thread 148 bound to OS proc set {132}
OMP: pid 11276 tid 11426 thread 72 bound to OS proc set {88}
OMP: pid 11276 tid 11438 thread 78 bound to OS proc set {94}
OMP: pid 11276 tid 11430 thread 74 bound to OS proc set {90}
OMP: pid 11276 tid 11464 thread 91 bound to OS proc set {67}
OMP: pid 11276 tid 11462 thread 90 bound to OS proc set {66}
OMP: pid 11276 tid 11290 thread 4 bound to OS proc set {4}
OMP: pid 11276 tid 11286 thread 2 bound to OS proc set {2}
OMP: pid 11276 tid 11458 thread 88 bound to OS proc set {64}
OMP: pid 11276 tid 11296 thread 7 bound to OS proc set {7}
OMP: pid 11276 tid 11568 thread 143 bound to OS proc set {183}
OMP: pid 11276 tid 11598 thread 158 bound to OS proc set {158}
OMP: pid 11276 tid 11594 thread 156 bound to OS proc set {156}
OMP: pid 11276 tid 11600 thread 159 bound to OS proc set {159}
OMP: pid 11276 tid 11436 thread 77 bound to OS proc set {93}
OMP: pid 11276 tid 11294 thread 6 bound to OS proc set {6}
OMP: pid 11276 tid 11428 thread 73 bound to OS proc set {89}
OMP: pid 11276 tid 11346 thread 32 bound to OS proc set {8}
OMP: pid 11276 tid 11350 thread 34 bound to OS proc set {10}
OMP: pid 11276 tid 11404 thread 61 bound to OS proc set {61}
OMP: pid 11276 tid 11348 thread 33 bound to OS proc set {9}
OMP: pid 11276 tid 11418 thread 68 bound to OS proc set {20}
OMP: pid 11276 tid 11420 thread 69 bound to OS proc set {21}
OMP: pid 11276 tid 11304 thread 11 bound to OS proc set {75}
OMP: pid 11276 tid 11302 thread 10 bound to OS proc set {74}
OMP: pid 11276 tid 11284 thread 1 bound to OS proc set {1}
OMP: pid 11276 tid 11352 thread 35 bound to OS proc set {11}
OMP: pid 11276 tid 11526 thread 122 bound to OS proc set {146}
OMP: pid 11276 tid 11298 thread 8 bound to OS proc set {72}
OMP: pid 11276 tid 11366 thread 42 bound to OS proc set {82}
OMP: pid 11276 tid 11306 thread 12 bound to OS proc set {76}
OMP: pid 11276 tid 11340 thread 29 bound to OS proc set {53}
OMP: pid 11276 tid 11584 thread 151 bound to OS proc set {135}
OMP: pid 11276 tid 11370 thread 44 bound to OS proc set {84}
OMP: pid 11276 tid 11582 thread 150 bound to OS proc set {134}
OMP: pid 11276 tid 11292 thread 5 bound to OS proc set {5}
OMP: pid 11276 tid 11310 thread 14 bound to OS proc set {78}
OMP: pid 11276 tid 11312 thread 15 bound to OS proc set {79}
OMP: pid 11276 tid 11454 thread 86 bound to OS proc set {46}
OMP: pid 11276 tid 11586 thread 152 bound to OS proc set {152}
OMP: pid 11276 tid 11356 thread 37 bound to OS proc set {13}
OMP: pid 11276 tid 11338 thread 28 bound to OS proc set {52}
OMP: pid 11276 tid 11372 thread 45 bound to OS proc set {85}
OMP: pid 11276 tid 11374 thread 46 bound to OS proc set {86}
OMP: pid 11276 tid 11592 thread 155 bound to OS proc set {155}
OMP: pid 11276 tid 11288 thread 3 bound to OS proc set {3}
OMP: pid 11276 tid 11354 thread 36 bound to OS proc set {12}
OMP: pid 11276 tid 11422 thread 70 bound to OS proc set {22}
OMP: pid 11276 tid 11362 thread 40 bound to OS proc set {80}
OMP: pid 11276 tid 11314 thread 16 bound to OS proc set {24}
OMP: pid 11276 tid 11316 thread 17 bound to OS proc set {25}
OMP: pid 11276 tid 11320 thread 19 bound to OS proc set {27}
OMP: pid 11276 tid 11342 thread 30 bound to OS proc set {54}
OMP: pid 11276 tid 11376 thread 47 bound to OS proc set {87}
OMP: pid 11276 tid 11336 thread 27 bound to OS proc set {51}
OMP: pid 11276 tid 11364 thread 41 bound to OS proc set {81}
OMP: pid 11276 tid 11588 thread 153 bound to OS proc set {153}
OMP: pid 11276 tid 11368 thread 43 bound to OS proc set {83}
OMP: pid 11276 tid 11334 thread 26 bound to OS proc set {50}
OMP: pid 11276 tid 11460 thread 89 bound to OS proc set {65}
OMP: pid 11276 tid 11328 thread 23 bound to OS proc set {31}
OMP: pid 11276 tid 11318 thread 18 bound to OS proc set {26}
OMP: pid 11276 tid 11308 thread 13 bound to OS proc set {77}
OMP: pid 11276 tid 11326 thread 22 bound to OS proc set {30}
OMP: pid 11276 tid 11332 thread 25 bound to OS proc set {49}
OMP: pid 11276 tid 11360 thread 39 bound to OS proc set {15}
OMP: pid 11276 tid 11322 thread 20 bound to OS proc set {28}
OMP: pid 11276 tid 11344 thread 31 bound to OS proc set {55}
OMP: pid 11276 tid 11330 thread 24 bound to OS proc set {48}
OMP: pid 11276 tid 11300 thread 9 bound to OS proc set {73}
OMP: pid 11276 tid 11596 thread 157 bound to OS proc set {157}
OMP: pid 11276 tid 11572 thread 145 bound to OS proc set {129}
OMP: pid 11276 tid 11324 thread 21 bound to OS proc set {29}
OMP: pid 11276 tid 11576 thread 147 bound to OS proc set {131}
OMP: pid 11276 tid 11590 thread 154 bound to OS proc set {154}
OMP: pid 11276 tid 11358 thread 38 bound to OS proc set {14}
what is a LLM? and why it’s changing the game
A Large Language Model (LLM) is a type of artificial intelligence (AI) that can process, understand, and generate human-like language. LLMs are trained on vast amounts of text data, which allows them to learn patterns, relationships, and context in language. This enables them to perform a wide range of tasks, including:
1. Answering questions: LLMs can comprehend natural language queries and provide relevant responses.
2. Generating text: LLMs can create text based on a given prompt or topic, often indistinguishable from text written by a human.
3. Translation: LLMs can translate text from one language to another, with varying degrees of accuracy.
4. Summarization: LLMs can condense long pieces of text into concise summaries.
5. Conversational dialogue: LLMs can engage in natural-sounding conversations, either as a chatbot or a conversational interface.
LLMs are changing the game in several industries:
1. **Customer service**: Chatbots powered by LLMs can provide 24/7 support, answering customer inquiries and resolving issues more efficiently than human customer support agents.
2. **Content creation**: LLMs can assist content creators, such as writers, journalists, and social media managers, by generating ideas, research, and even entire articles.
3. **Language learning**: LLMs can help language learners by providing personalized feedback, suggesting corrections, and even generating language lessons.
4. **Research**: LLMs can aid researchers by analyzing large volumes of text data, identifying patterns, and suggesting new research directions.
5. **Education**: LLMs can assist educators by generating customized learning materials, grading assignments, and even providing one-on-one tutoring.
6. **Marketing**: LLMs can help marketers by generating targeted content, analyzing customer sentiment, and optimizing marketing campaigns.
7. **Healthcare**: LLMs can assist healthcare professionals by analyzing medical literature, suggesting diagnoses, and even generating treatment plans.
LLMs are also raising important questions and concerns, such as:
1. **Job displacement**: Will LLMs replace human professionals in various industries?
2. **Bias and accuracy**: Can LLMs inherit biases from the data they're trained on, and how accurate are their responses?
3. **Accountability**: Who is responsible when LLMs provide incorrect or misleading information?
4. **Ethics**: How should LLMs be designed and
Your experiment path is /beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_5
To display your profiling results:
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# LEVEL | REPORT | COMMAND #
##########################################################################################################################################################################################################################
# Functions | Cluster-wide | maqao lprof -df xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_5 #
# Functions | Per-node | maqao lprof -df -dn xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_5 #
# Functions | Per-process | maqao lprof -df -dp xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_5 #
# Functions | Per-thread | maqao lprof -df -dt xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_5 #
# Loops | Cluster-wide | maqao lprof -dl xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_5 #
# Loops | Per-node | maqao lprof -dl -dn xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_5 #
# Loops | Per-process | maqao lprof -dl -dp xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_5 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/beegfs/hackathon/users/eoseret/qaas_runs_test/175-950-2189/intel/llama.cpp/run/oneview_runs/multicore/icx_3/oneview_results_1759511881/tools/lprof_npsu_run_5 #
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