high performance computing on graphics processing units: hgpu.org

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FZ-GPU: A Fast and High-Ratio Lossy Compressor for Scientific Computing Applications on GPUs

Boyuan Zhang, Jiannan Tian, Sheng Di, Xiaodong Yu, Yunhe Feng, Xin Liang, Dingwen Tao, Franck Cappello

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, nVidia A100, nVidia RTX A4000, Package, Signal processing

May 7, 2023 by hgpu

Simple and efficient GPU accelerated topology optimisation: Codes and applications

Erik A. Träff, Anton Rydahl, Sven Karlsson, Ole Sigmund, Niels Aage

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Tags: Computer science, CUDA, nVidia, nVidia A100, OpenCL, OpenMP, Package, Topology optimization problem

April 23, 2023 by hgpu

Thread-safe lattice Boltzmann for high-performance computing on GPUs

Andrea Montessori, Marco Lauricella, Adriano Tiribocchi, Mihir Durve, Michele La Rocca, Giorgio Amati, Fabio Bonaccorso, Sauro Succi

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Tags: Algorithms, cfd, CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia A100, Package

April 23, 2023 by hgpu

GPULZ: Optimizing LZSS Lossless Compression for Multi-byte Data on Modern GPUs

Boyuan Zhang, Jiannan Tian, Sheng Di, Xiaodong Yu, Martin Swany, Dingwen Tao, Franck Cappello

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, nVidia A100, nVidia RTX A4000, Package

April 23, 2023 by hgpu

Portability and Scalability of OpenMP Offloading on State-of-the-art Accelerators

Yehonatan Fridman, Guy Tamir, Gal Oren

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Tags: Benchmarking, Computer science, Intel, Intel Ponte Vecchio Max 1100, nVidia, nVidia A100, oneAPI, OpenMP, Package, performance portability

April 16, 2023 by hgpu

PopSparse: Accelerated block sparse matrix multiplication on IPU

Zhiyi Li, Douglas Orr, Valeriu Ohan, Godfrey Da costa, Tom Murray, Adam Sanders, Deniz Beker, Dominic Masters

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Tags: Computer science, CUDA, Deep learning, Linear Algebra, Machine learning, Matrix multiplication, nVidia, nVidia A100, Package, Sparse matrix

April 2, 2023 by hgpu

Pgx: Hardware-accelerated parallel game simulation for reinforcement learning

Sotetsu Koyamada, Shinri Okano, Soichiro Nishimori, Yu Murata, Keigo Habara, Haruka Kita, Shin Ishii

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Tags: Artificial intelligence, Computer science, Deep learning, nVidia, nVidia A100, Package

April 2, 2023 by hgpu

Kernel Launcher: C++ Library for Optimal-Performance Portable CUDA Applications

Stijn Heldens, Ben van Werkhoven

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Tags: Computer science, CUDA, Fluid dynamics, nVidia, nVidia A100, Package, Performance, performance portability

March 26, 2023 by hgpu

Stellar Mergers with HPX-Kokkos and SYCL: Methods of using an Asynchronous Many-Task Runtime System with SYCL

Gregor Daiß, Patrick Diehl, Hartmut Kaiser, Dirk Pflüger

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Tags: AMD Radeon Instinct MI100, Astrophysics, Computer science, CUDA, HIP, nVidia, nVidia A100, Package, SYCL

March 19, 2023 by hgpu

Harmonic CUDA: Asynchronous Programming on GPUs

Jonathan Wapman, Sean Treichler, Serban D. Porumbescu, John D. Owens

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Tags: Computer science, CUDA, GEMM, Linear Algebra, Matrix multiplication, nVidia, nVidia A100

March 5, 2023 by hgpu

Revisiting Query Performance in GPU Database Systems

Jiashen Cao, Rathijit Sen, Matteo Interlandi, Joy Arulraj, Hyesoon Kim

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Tags: Computer science, CUDA, Databases, nVidia, nVidia A100

February 5, 2023 by hgpu

Analyzing Resource Utilization in an HPC System: A Case Study of NERSC’s Perlmutter

Jie Li, George Michelogiannakis, Brandon Cook, Dulanya Cooray, Yong Chen

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Tags: Computer science, HPC, nVidia, nVidia A100, Performance

January 22, 2023 by hgpu

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

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

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

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

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

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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high performance computing on graphics processing units: hgpu.org

FZ-GPU: A Fast and High-Ratio Lossy Compressor for Scientific Computing Applications on GPUs

Simple and efficient GPU accelerated topology optimisation: Codes and applications

Thread-safe lattice Boltzmann for high-performance computing on GPUs

GPULZ: Optimizing LZSS Lossless Compression for Multi-byte Data on Modern GPUs

Portability and Scalability of OpenMP Offloading on State-of-the-art Accelerators

PopSparse: Accelerated block sparse matrix multiplication on IPU

Pgx: Hardware-accelerated parallel game simulation for reinforcement learning

Kernel Launcher: C++ Library for Optimal-Performance Portable CUDA Applications

Stellar Mergers with HPX-Kokkos and SYCL: Methods of using an Asynchronous Many-Task Runtime System with SYCL

Harmonic CUDA: Asynchronous Programming on GPUs

Revisiting Query Performance in GPU Database Systems

Analyzing Resource Utilization in an HPC System: A Case Study of NERSC’s Perlmutter

Recent source codes

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

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

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

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

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

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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