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DTSTART;TZID=America/Denver:20231113T090000
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UID:submissions.supercomputing.org_SC23_sess443@linklings.com
SUMMARY:AI Assisted Software Development for HPC (AI4DEV)
DESCRIPTION:MPI-RICAL: Data-Driven MPI Distributed Parallelism Assistance 
 with Transformers\n\nMessage Passing Interface (MPI) plays a crucial role 
 in distributed memory parallelization across multiple nodes. However, para
 llelizing MPI code manually, and specifically, performing domain decomposi
 tion, is a challenging, error-prone task. In this paper, we address this p
 roblem by developing MPI-...\n\n\nNadav Schneider and Tal Kadosh (Ben-Guri
 on University of the Negev, Israel; IAEC); Niranjan Hasabnis and Timothy M
 attson (Intel Labs); Yuval Pinter (Ben-Gurion University of the Negev, Isr
 ael); and Gal Oren (Technion - Israel Institute of Technology)\n----------
 -----------\nUnlocking the Potential of Large Language Models for High-Per
 formance Computing Code\n\nHigh-Performance Computing (HPC) has long been 
 the driving force behind advancements in science, engineering, and beyond.
  Yet, realizing the full potential of HPC applications has often been hamp
 ered by the intricate nature of programming for the underlying parallel sy
 stems. In this keynote, we expl...\n\n\nGal Oren (Technion - Israel Instit
 ute of Technology)\n---------------------\nVSCuda: LLM-Based CUDA Extensio
 n for Visual Studio Code\n\nSince CUDA was introduced around 15 years ago,
  it  has developed constantly to accommodate many different functionalitie
 s. For beginners in particular, it is already difficult remember the expec
 ted function parameters of commonly used CUDA features, let alone optimize
  their code by exploiting these ...\n\n\nBrian Chen, Nafis Mustakin, Alvin
  Hoang, Sakib Fuad, and Daniel Wong (University of California, Riverside)\
 n---------------------\nAI-Driven Performance Metaprogramming\n\nRecent ad
 vances in artificial intelligence methods show the enormous potential of A
 I methods. The underlying concepts are embedding spaces to represent real-
 world information. These embedding spaces have been used to represent, tra
 nsform, and work with complex information in large-language models bu...\n
 \n\nTorsten Hoefler (ETHZ)\n---------------------\nAI4DEV – Morning Break\
 n---------------------\nLLVM in the Age of LLMs:  Machine Learning for IR 
 and Optimization and More\n\nWilliam S. Moses (University of Illinois)\n--
 -------------------\nOpening Remarks\n\nOpening remarks for the AI4DEV Wor
 kshop\n\n\nIgnacio Laguna (Lawrence Livermore National Laboratory (LLNL))\
 n\nTag: Artificial Intelligence/Machine Learning, Software Engineering\n\n
 Registration Category: Workshop Reg Pass\n\nSession Chairs: Giorgis Georga
 koudis (Lawrence Livermore National Laboratory (LLNL)), Ignacio Laguna (La
 wrence Livermore National Laboratory (LLNL)), and Konstantinos Parasyris (
 Lawrence Livermore National Laboratory (LLNL))
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