high performance computing on graphics processing units: hgpu.org

Filippo Vicentini, Damian Hofmann, Attila Szabo, Dian Wu, Christopher Roth, Clemens Giuliani, Gabriel Pescia, Jannes Nys, Vladimir Vargas-Calderon, Nikita Astrakhantsev, Giuseppe Carleo

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Tags: Linear Algebra, Machine learning, Neural networks, nVidia, nVidia GeForce RTX 3090, Package, Physics, Python, Quantum Physics, Tesla A100

December 26, 2021 by hgpu

A Study of Mixed Precision Strategies for GMRES on GPUs

Jennifer A. Loe, Christian A. Glusa, Ichitaro Yamazaki, Erik G. Boman, Sivasankaran Rajamanickam

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, Mixed precision, nVidia, performance portability, Tesla V100

September 19, 2021 by hgpu

Block Conjugate Gradient Solver in OpenCL

Kert Tali, Eero Vainikko

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Tags: Algorithms, Computer science, Conjugate gradient solver, Linear Algebra, nVidia, nVidia GeForce RTX 2080, OpenCL

July 11, 2021 by hgpu

Experimental Evaluation of Multiprecision Strategies for GMRES on GPUs

Jennifer A. Loe, Christian A. Glusa, Ichitaro Yamazaki, Erik G. Boman, Sivasankaran Rajamanickam

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Tags: Algorithms, CUDA, Linear Algebra, Mathematics, Numerical Analysis, nVidia, performance portability, Tesla V100

May 23, 2021 by hgpu

NPBench: A Benchmarking Suite for High-Performance NumPy

Alexandros Nikolaos Ziogas, Tal Ben-Nun, Timo Schneider, Torsten Hoefler

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Tags: Benchmarking, Computer science, CUDA, HPC, Linear Algebra, nVidia, Package, Performance, Python, Tesla V100

May 16, 2021 by hgpu

CryptGPU: Fast Privacy-Preserving Machine Learning on the GPU

Sijun Tan, Brian Knott, Yuan Tian, David J. Wu

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Tags: Computer science, CUDA, Deep learning, Linear Algebra, Machine learning, Neural networks, nVidia, Package, PyTorch, Security, Tesla V100

April 25, 2021 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

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

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

Efficient Quantized Sparse Matrix Operations on Tensor Cores

Exploiting dynamic sparse matrices for performance portable linear algebra operations

DarKnight: An Accelerated Framework for Privacy and Integrity Preserving Deep Learning Using Trusted Hardware

Performance study on GPU offloading techniques using the Gauss matrix inverse algorithm

Bit-GraphBLAS: Bit-Level Optimizations of Matrix-Centric Graph Processing on GPU

FSpGEMM: An OpenCL-based HPC Framework for Accelerating General Sparse Matrix-Matrix Multiplication on FPGAs

NetKet 3: Machine Learning Toolbox for Many-Body Quantum Systems

A Study of Mixed Precision Strategies for GMRES on GPUs

Block Conjugate Gradient Solver in OpenCL

Experimental Evaluation of Multiprecision Strategies for GMRES on GPUs

NPBench: A Benchmarking Suite for High-Performance NumPy

CryptGPU: Fast Privacy-Preserving Machine Learning on the GPU

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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