high performance computing on graphics processing units: hgpu.org

Krishna Teja Chitty-Venkata, Siddhisanket Raskar, Bharat Kale, Farah Ferdaus, Aditya Tanikanti, Ken Raffenetti, Valerie Taylor, Murali Emani, Venkatram Vishwanath

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Tags: AI, AMD Radeon Instinct MI250, AMD Radeon Instinct MI300X, Artificial intelligence, ATI, Benchmarking, Computer science, CUDA, LLM, Machine learning, nVidia, nVidia A100, nVidia GH200, nVidia H100, OpenCL, Performance

November 10, 2024 by hgpu

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

Pascal Jahan Elahi

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Tags: Computer science, CUDA, MPI, nVidia, nVidia GH200, OpenMP, Package, Performance

November 10, 2024 by hgpu

Portability of Fortran’s ‘do concurrent’ on GPUs

Ronald M. Caplan, Miko M. Stulajter, Jon A. Linker, Jeff Larkin, Henry A. Gabb, Shiquan Su, Ivan Rodriguez, Zachary Tschirhart, Nicholas Malaya

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Tags: Computer science, Fortran, Intel, Intel Data Center GPU Max 1550, Intel Ponte Vecchio Max 1100, nVidia, nVidia A100, nVidia GH200, nVidia H100, OpenACC, OpenMP, Package

August 18, 2024 by hgpu

Automatic BLAS Offloading on Unified Memory Architecture: A Study on NVIDIA Grace-Hopper

Junjie Li, Yinzhi Wang, Xiao Liang, Hang Liu

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Tags: BLAS, Chemistry, CUDA, nVidia, nVidia GH200, nVidia H100, Performance, Physics

May 5, 2024 by hgpu

hpcbench: A set of benchmarking utilities for biomolecular simulation tools

Engineering Supercomputing Platforms for Biomolecular Applications

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

See all packages

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high performance computing on graphics processing units: hgpu.org

Engineering Supercomputing Platforms for Biomolecular Applications

chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations

Acceleration as a Service (XaaS) Source Containers

Performant Automatic BLAS Offloading on Unified Memory Architecture with OpenMP First-Touch Style Data Movement

Unified schemes for directive-based GPU offloading

A Distributed-memory Tridiagonal Solver Based on a Specialised Data Structure Optimised for CPU and GPU Architectures

LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

Portability of Fortran’s ‘do concurrent’ on GPUs

Automatic BLAS Offloading on Unified Memory Architecture: A Study on NVIDIA Grace-Hopper

Recent source codes

hpcbench: A set of benchmarking utilities for biomolecular simulation tools

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

chemtrain: Training Molecular Dynamics Potentials in JAX

microSYCL: SYCL micro-benchmarks repository

XaaS containers

CASS: Cuda-Amd aSSembly

Cluser of smartphones for edge computing application using TensorFlow

SYCL Container

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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