high performance computing on graphics processing units: hgpu.org

Ka Hei Martin Kwok, Matti Kortelainen, Giuseppe Cerati, Alexei Strelchenko, Oliver Gutsche, Allison Reinsvold Hall, Steve Lantz, Michael Reid, Daniel Riley, Sophie Berkman, Seyong Lee, Hammad Ather, Boyana Norris, Cong Wang

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Tags: AMD Radeon Instinct MI100, ATI, HEP, Intel, Intel Arc A770, nVidia, nVidia A100, nVidia V100, OpenMP, performance portability, Physics, SYCL

January 28, 2024 by hgpu

BANG: Billion-Scale Approximate Nearest Neighbor Search using a Single GPU

Karthik V., Saim Khan, Somesh Singh, Harsha Vardhan Simhadri, Jyothi Vedurada

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Tags: Computer science, CUDA, Nearest neighbour, nVidia, nVidia A100

January 28, 2024 by hgpu

HAP: SPMD DNN Training on Heterogeneous GPU Clusters with Automated Program Synthesis

Shiwei Zhang, Lansong Diao, Chuan Wu, Zongyan Cao, Siyu Wang, Wei Lin

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Tags: Computer science, CUDA, Deep learning, Distributed computing, GPU cluster, nVidia, nVidia A100, nVidia P100, nVidia V100, Package, PyTorch

January 14, 2024 by hgpu

Orion: Interference-aware, Fine-grained GPU Sharing for ML Applications

Foteini Strati, Xianzhe Ma, Ana Klimovic

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia A100, nVidia V100, Package, PyTorch

January 14, 2024 by hgpu

Enabling Quantum Computer Simulations on AMD GPUs: a HIP Backend for Google’s qsim

Stefano Markidis

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Tags: AMD Radeon Instinct MI250X, Computer science, CUDA, HIP, nVidia, nVidia A100, Quantum computing

December 31, 2023 by hgpu

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high performance computing on graphics processing units: hgpu.org

Sustainable Supercomputing for AI: GPU Power Capping at HPC Scale

Benchmarking and Dissecting the Nvidia Hopper GPU Architecture

QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference

DeepSeek-Coder: When the Large Language Model Meets Programming – The Rise of Code Intelligence

Out of kernel tuning and optimizations for portable large-scale docking experiments on GPUs

Towards a GPU-Parallelization of the neXtSIM-DG Dynamical Core

High-order thread-safe lattice Boltzmann model for HPC turbulent flow simulations

Application of performance portability solutions for GPUs and many-core CPUs to track reconstruction kernels

BANG: Billion-Scale Approximate Nearest Neighbor Search using a Single GPU

HAP: SPMD DNN Training on Heterogeneous GPU Clusters with Automated Program Synthesis

Orion: Interference-aware, Fine-grained GPU Sharing for ML Applications

Enabling Quantum Computer Simulations on AMD GPUs: a HIP Backend for Google’s qsim

Recent source codes

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

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Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

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Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

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