* [MAQAO] Info: Detected 1 Lprof instances in ortce-gh.
If this is incorrect, rerun with number-processes-per-node=X
OMP: pid 93670 tid 93691 thread 18 bound to OS proc set {18}
OMP: pid 93670 tid 93686 thread 13 bound to OS proc set {13}
OMP: pid 93670 tid 93722 thread 49 bound to OS proc set {49}
OMP: pid 93670 tid 93670 thread 0 bound to OS proc set {0}
OMP: pid 93670 tid 93723 thread 50 bound to OS proc set {50}
OMP: pid 93670 tid 93721 thread 48 bound to OS proc set {48}
OMP: pid 93670 tid 93724 thread 51 bound to OS proc set {51}
OMP: pid 93670 tid 93739 thread 66 bound to OS proc set {66}
OMP: pid 93670 tid 93737 thread 64 bound to OS proc set {64}
OMP: pid 93670 tid 93697 thread 24 bound to OS proc set {24}
OMP: pid 93670 tid 93738 thread 65 bound to OS proc set {65}
OMP: pid 93670 tid 93696 thread 23 bound to OS proc set {23}
OMP: pid 93670 tid 93720 thread 47 bound to OS proc set {47}
OMP: pid 93670 tid 93706 thread 33 bound to OS proc set {33}
OMP: pid 93670 tid 93692 thread 19 bound to OS proc set {19}
OMP: pid 93670 tid 93718 thread 45 bound to OS proc set {45}
OMP: pid 93670 tid 93728 thread 55 bound to OS proc set {55}
OMP: pid 93670 tid 93712 thread 39 bound to OS proc set {39}
OMP: pid 93670 tid 93700 thread 27 bound to OS proc set {27}
OMP: pid 93670 tid 93726 thread 53 bound to OS proc set {53}
OMP: pid 93670 tid 93685 thread 12 bound to OS proc set {12}
OMP: pid 93670 tid 93694 thread 21 bound to OS proc set {21}
OMP: pid 93670 tid 93725 thread 52 bound to OS proc set {52}
OMP: pid 93670 tid 93690 thread 17 bound to OS proc set {17}
OMP: pid 93670 tid 93704 thread 31 bound to OS proc set {31}
OMP: pid 93670 tid 93707 thread 34 bound to OS proc set {34}
OMP: pid 93670 tid 93741 thread 68 bound to OS proc set {68}
OMP: pid 93670 tid 93708 thread 35 bound to OS proc set {35}
OMP: pid 93670 tid 93730 thread 57 bound to OS proc set {57}
OMP: pid 93670 tid 93719 thread 46 bound to OS proc set {46}
OMP: pid 93670 tid 93743 thread 70 bound to OS proc set {70}
OMP: pid 93670 tid 93705 thread 32 bound to OS proc set {32}
OMP: pid 93670 tid 93735 thread 62 bound to OS proc set {62}
OMP: pid 93670 tid 93698 thread 25 bound to OS proc set {25}
OMP: pid 93670 tid 93733 thread 60 bound to OS proc set {60}
OMP: pid 93670 tid 93731 thread 58 bound to OS proc set {58}
OMP: pid 93670 tid 93676 thread 3 bound to OS proc set {3}
OMP: pid 93670 tid 93688 thread 15 bound to OS proc set {15}
OMP: pid 93670 tid 93714 thread 41 bound to OS proc set {41}
OMP: pid 93670 tid 93732 thread 59 bound to OS proc set {59}
OMP: pid 93670 tid 93689 thread 16 bound to OS proc set {16}
OMP: pid 93670 tid 93742 thread 69 bound to OS proc set {69}
OMP: pid 93670 tid 93683 thread 10 bound to OS proc set {10}
OMP: pid 93670 tid 93684 thread 11 bound to OS proc set {11}
OMP: pid 93670 tid 93734 thread 61 bound to OS proc set {61}
OMP: pid 93670 tid 93703 thread 30 bound to OS proc set {30}
OMP: pid 93670 tid 93736 thread 63 bound to OS proc set {63}
OMP: pid 93670 tid 93687 thread 14 bound to OS proc set {14}
OMP: pid 93670 tid 93678 thread 5 bound to OS proc set {5}
OMP: pid 93670 tid 93711 thread 38 bound to OS proc set {38}
OMP: pid 93670 tid 93717 thread 44 bound to OS proc set {44}
OMP: pid 93670 tid 93677 thread 4 bound to OS proc set {4}
OMP: pid 93670 tid 93740 thread 67 bound to OS proc set {67}
OMP: pid 93670 tid 93727 thread 54 bound to OS proc set {54}
OMP: pid 93670 tid 93744 thread 71 bound to OS proc set {71}
OMP: pid 93670 tid 93709 thread 36 bound to OS proc set {36}
OMP: pid 93670 tid 93680 thread 7 bound to OS proc set {7}
OMP: pid 93670 tid 93675 thread 2 bound to OS proc set {2}
OMP: pid 93670 tid 93729 thread 56 bound to OS proc set {56}
OMP: pid 93670 tid 93702 thread 29 bound to OS proc set {29}
OMP: pid 93670 tid 93713 thread 40 bound to OS proc set {40}
OMP: pid 93670 tid 93682 thread 9 bound to OS proc set {9}
OMP: pid 93670 tid 93674 thread 1 bound to OS proc set {1}
OMP: pid 93670 tid 93699 thread 26 bound to OS proc set {26}
OMP: pid 93670 tid 93681 thread 8 bound to OS proc set {8}
OMP: pid 93670 tid 93693 thread 20 bound to OS proc set {20}
OMP: pid 93670 tid 93716 thread 43 bound to OS proc set {43}
OMP: pid 93670 tid 93701 thread 28 bound to OS proc set {28}
OMP: pid 93670 tid 93715 thread 42 bound to OS proc set {42}
OMP: pid 93670 tid 93710 thread 37 bound to OS proc set {37}
OMP: pid 93670 tid 93679 thread 6 bound to OS proc set {6}
OMP: pid 93670 tid 93695 thread 22 bound to OS proc set {22}
what is a LLM? and why should i care?
A Large Language Model (LLM) is a type of artificial intelligence (AI) that can process and generate human-like text based on the input it receives. LLMs are trained on vast amounts of text data, which allows them to learn patterns, relationships, and context in language. This enables them to generate coherent and often informative responses to user queries.
Here are some reasons why you should care about LLMs:
1. **Improved search and content generation:** LLMs can help improve search results by providing more accurate and relevant information. They can also generate content such as articles, blog posts, and even entire books.
2. **Personalized experiences:** LLMs can be used to create personalized experiences for users. For example, they can generate customized news feeds, product recommendations, or even entire stories based on a user's interests and preferences.
3. **Customer support:** LLMs can be used to provide 24/7 customer support by answering frequently asked questions, helping with simple transactions, and even handling complex issues.
4. **Language learning:** LLMs can help language learners by providing personalized feedback, practicing conversations, and even generating language learning materials.
5. **Content creation:** LLMs can be used to create content such as dialogue, scripts, and even entire stories. This can help writers, filmmakers, and other creators to generate ideas and develop their projects.
Some popular examples of LLMs include:
1. **Chatbots:** Many companies use LLMs to power their chatbots, which can help customers with simple transactions, answer frequently asked questions, and even provide customer support.
2. **Virtual assistants:** LLMs are used in virtual assistants like Siri, Google Assistant, and Alexa to provide information, set reminders, and even control smart home devices.
3. **Language translation:** LLMs are used in language translation tools like Google Translate to provide accurate and context-specific translations.
Overall, LLMs have the potential to revolutionize the way we interact with technology, from simple tasks like search and customer support to more complex tasks like content creation and language learning. As LLMs continue to evolve, we can expect to see even more innovative applications and uses for these powerful tools. [end of text]
Your experiment path is /scratch/users/amazouz/QAAS/service/Llama.cpp/ortce-gh/175-931-3387/llama.cpp/run/oneview_runs/compilers/armclang_3/oneview_results_1759315561/tools/lprof_npsu_run_0
To display your profiling results:
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# LEVEL | REPORT | COMMAND #
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# Functions | Cluster-wide | maqao lprof -df xp=/scratch/users/amazouz/QAAS/service/Llama.cpp/ortce-gh/175-931-3387/llama.cpp/run/oneview_runs/compilers/armclang_3/oneview_results_1759315561/tools/lprof_npsu_run_0 #
# Functions | Per-node | maqao lprof -df -dn xp=/scratch/users/amazouz/QAAS/service/Llama.cpp/ortce-gh/175-931-3387/llama.cpp/run/oneview_runs/compilers/armclang_3/oneview_results_1759315561/tools/lprof_npsu_run_0 #
# Functions | Per-process | maqao lprof -df -dp xp=/scratch/users/amazouz/QAAS/service/Llama.cpp/ortce-gh/175-931-3387/llama.cpp/run/oneview_runs/compilers/armclang_3/oneview_results_1759315561/tools/lprof_npsu_run_0 #
# Functions | Per-thread | maqao lprof -df -dt xp=/scratch/users/amazouz/QAAS/service/Llama.cpp/ortce-gh/175-931-3387/llama.cpp/run/oneview_runs/compilers/armclang_3/oneview_results_1759315561/tools/lprof_npsu_run_0 #
# Loops | Cluster-wide | maqao lprof -dl xp=/scratch/users/amazouz/QAAS/service/Llama.cpp/ortce-gh/175-931-3387/llama.cpp/run/oneview_runs/compilers/armclang_3/oneview_results_1759315561/tools/lprof_npsu_run_0 #
# Loops | Per-node | maqao lprof -dl -dn xp=/scratch/users/amazouz/QAAS/service/Llama.cpp/ortce-gh/175-931-3387/llama.cpp/run/oneview_runs/compilers/armclang_3/oneview_results_1759315561/tools/lprof_npsu_run_0 #
# Loops | Per-process | maqao lprof -dl -dp xp=/scratch/users/amazouz/QAAS/service/Llama.cpp/ortce-gh/175-931-3387/llama.cpp/run/oneview_runs/compilers/armclang_3/oneview_results_1759315561/tools/lprof_npsu_run_0 #
# Loops | Per-thread | maqao lprof -dl -dt xp=/scratch/users/amazouz/QAAS/service/Llama.cpp/ortce-gh/175-931-3387/llama.cpp/run/oneview_runs/compilers/armclang_3/oneview_results_1759315561/tools/lprof_npsu_run_0 #
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