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DTSTAMP:20260422T143138Z
LOCATION:B313
DTSTART;TZID=America/New_York:20241118T121000
DTEND;TZID=America/New_York:20241118T123000
UID:submissions.supercomputing.org_SC24_sess757_ws_ai4s101@linklings.com
SUMMARY:ChatBLAS: The First AI-Generated and Portable BLAS Library
DESCRIPTION:Pedro Valero-Lara, William Godoy, Keita Teranishi, Prasanna Ba
 laprakash, and Jeffrey Vetter (Oak Ridge National Laboratory (ORNL))\n\nWe
  present ChatBLAS, the first AI-generated and portable Basic Linear Algebr
 a Subprograms (BLAS) library on different CPU/GPU configurations. The purp
 ose of this study is (i) to evaluate the capabilities of current large lan
 guage models (LLMs) to generate a portable and HPC library for BLAS operat
 ions and (ii) to define the fundamental practices and criteria to interact
  with LLMs for HPC targets to elevate the trustworthiness and performance 
 levels of the AI-generated\nHPC codes. The generated C/C++ codes must be h
 ighly optimized using device-specific solutions to reach high levels of pe
 rformance. Additionally, these codes are very algorithm-dependent, thereby
  adding an extra dimension of complexity to this study. We used OpenAI’s L
 LM ChatGPT and focused on vector-vector BLAS level-1 operations.ChatBLAS c
 an generate functional and correct codes, thereby achieving high trustwort
 hiness levels, and can compete or even provide\nbetter performance against
  vendor libraries.\n\nTag: Artificial Intelligence/Machine Learning\n\nReg
 istration Category: Workshop Reg Pass\n\nSession Chairs: Murali Emani (Arg
 onne National Laboratory (ANL)); Gokcen Kestor (Barcelona Supercomputing C
 enter (BSC); University of California, Merced); and Dong Li (University of
  California, Merced)\n\n
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