high performance computing on graphics processing units: hgpu.org

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Domain-Specific Code Language Models: Unraveling the Potential for HPC Codes and Tasks

Tal Kadosh, Niranjan Hasabnis, Vy A. Vo, Nadav Schneider, Neva Krien, Mihai Capota, Abdul Wasay, Nesreen Ahmed, Ted Willke, Guy Tamir, Yuval Pinter, Timothy Mattson, Gal Oren

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Tags: AI, Code generation, Computer science, Heterogeneous systems, HPC, nVidia, nVidia A40, OpenMP, Package, Python

January 7, 2024 by hgpu

Gaiwan: a Size-Polymorphic Typesystem for GPU Programs

Robbert Gurdeep Singha, Christophe Scholliers

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Tags: Benchmarking, Computer science, nVidia, nVidia A100, OpenCL, Package, Programming Languages

December 31, 2023 by hgpu

FCBench: Cross-Domain Benchmarking of Lossless Compression for Floating-Point Data

Xinyu Chen, Jiannan Tian, Ian Beaver, Cynthia Freeman, Yan Yan, Jianguo Wang, Dingwen Tao

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Tags: Benchmarking, Compression, Computer science, CUDA, Databases, HPC, nVidia, nVidia RTX 6000 Ada, Package, SYCL

December 24, 2023 by hgpu

Scalable Tuning of (OpenMP) GPU Applications via Kernel Record and Replay

Konstantinos Parasyris, Giorgis Georgakoudis, Esteban Rangel, Ignacio Laguna, Johannes Doerfert

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Tags: AMD Radeon Instinct MI250X, ATI, Auto-Tuning, Computer science, Heterogeneous systems, nVidia, nVidia V100, OpenMP, Package

December 18, 2023 by hgpu

Application Performance Profiling on Intel GPUs with Oneprof and Onetrace

Mariam Umar, Maxwell Jong

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Tags: Computer science, Intel, Intel Data Center GPU Max 1550, OpenCL, OpenMP, Package, Performance

December 18, 2023 by hgpu

Principles for Automated and Reproducible Benchmarking

Tuomas Koskela, Ilektra Christidi, Mosè Giordano, Emily Dubrovska, Jamie Quinn, Christopher Maynard, Dave Case, Kaan Olgu, Tom Deakin

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Tags: Benchmarking, Computer science, HPC, nVidia, oneAPI, Package, performance portability

December 18, 2023 by hgpu

Efficiently Processing Large Relational Joins on GPUs

Bowen Wu, Dimitrios Koutsoukos, Gustavo Alonso

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Tags: Benchmarking, Computer science, CUDA, Databases, nVidia, nVidia A100, nVidia GeForce RTX 3090, Package

December 10, 2023 by hgpu

GenVectorX: A performance-portable SYCL library for Lorentz Vectors operations

Monica Dessole, Jolly Chen, Axel Naumann

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Tags: CUDA, nVidia, nVidia A100, nVidia GeForce RTX 3060, nVidia L4, oneAPI, Package, Performance, Physics, SYCL

December 10, 2023 by hgpu

Testing and Mutation Testing for GPU Kernels

Yujie Liu

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Tags: Benchmarking, Computer science, CUDA, nVidia, Package, Performance, Thesis

December 3, 2023 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

Jun Chen, Xule Zhou, Hyesoon Kim

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Tags: AMD Radeon Instinct MI210, ATI, Code generation, Computer science, CUDA, HIP, nVidia, OpenCL, Package

December 3, 2023 by hgpu

Accelerating bioinformatics applications on CUDA-enabled multi-GPU systems

Robin Kobus

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Tags: Bioinformatics, Biology, CUDA, Databases, Hashing, nVidia, nVidia Quadro GV100, Package, Sequence alignment, Tesla P100, Tesla V100, Thesis

November 27, 2023 by hgpu

Evaluation of FPGA-based high performance computing platforms

Martin Frick-Lundgren

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Tags: Computer science, FPGA, HPC, Intel, Intel UHD 630, Matrix multiplication, OpenCL, Package, SYCL, Thesis

November 27, 2023 by hgpu

AutoDock-GPU: AutoDock for GPUs and other accelerators

Architecting Tensor Core-Based Reductions for Irregular Molecular Docking Kernels

NCCLX: collective communication framework

Collective Communication for 100k+ GPUs

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

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high performance computing on graphics processing units: hgpu.org

Packages

Domain-Specific Code Language Models: Unraveling the Potential for HPC Codes and Tasks

Gaiwan: a Size-Polymorphic Typesystem for GPU Programs

FCBench: Cross-Domain Benchmarking of Lossless Compression for Floating-Point Data

Scalable Tuning of (OpenMP) GPU Applications via Kernel Record and Replay

Application Performance Profiling on Intel GPUs with Oneprof and Onetrace

Principles for Automated and Reproducible Benchmarking

Efficiently Processing Large Relational Joins on GPUs

GenVectorX: A performance-portable SYCL library for Lorentz Vectors operations

Testing and Mutation Testing for GPU Kernels

CuPBoP-AMD: Extending CUDA to AMD Platforms

Accelerating bioinformatics applications on CUDA-enabled multi-GPU systems

Evaluation of FPGA-based high performance computing platforms

Recent source codes

AutoDock-GPU: AutoDock for GPUs and other accelerators

NCCLX: collective communication framework

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

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