high performance computing on graphics processing units: hgpu.org

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Benchmarking Intel Xeon Phi to Guide Kernel Design

Jianbin Fang, Ana Lucia Varbanescu, Henk Sips, Lilun Zhang, Yonggang Che, Chuanfu Xu

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Tags: Benchmarking, Computer science, Intel, Intel Phi, Performance

July 14, 2013 by hgpu

Comparative study of parallel programming models for multicore computing

Akhtar Ali

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Tags: Benchmarking, Computer science, DSP, Heterogeneous systems, nVidia, OpenCL, OpenMP, Tesla M2050, Thesis

July 7, 2013 by hgpu

Towards Rapid Prototyping of Parallel and HPC Applications (GPU Focus)

Mohammed S. Al-Mahfoudh

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 440, Thesis

June 28, 2013 by hgpu

GPUburn: A System to Test and Mitigate GPU Hardware Failures

David Defour, Eric Petit

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Tags: Benchmarking, Computer science, CUDA, Fault tolerance, nVidia, OpenCL, Tesla D870

June 2, 2013 by hgpu

Performance Tradeoff Spectrum of Integer and Floating Point Applications

M.G.B. Johnson, D. P. Playne, K.A. Hawick

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 590, nVidia GeForce GTX 680, Performance, Tesla C2050, Tesla C2070

May 30, 2013 by hgpu

Composing multiple StarPU applications over heterogeneous machines: a supervised approach

A.-E Hugo A. Guermouche P.-A. Wacrenier R. Namyst

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, Tesla M2070

May 23, 2013 by hgpu

Evaluating the Performance of Legacy Applications on Emerging Parallel Architectures

Simon John Pennycook

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Tags: Algorithms, ATI, ATI FirePro V7800, Benchmarking, Computer science, CUDA, MPI, nVidia, nVidia GeForce 8400 GS, nVidia GeForce 9800 GT, nVidia GeForce GTX 680, OpenCL, Performance, Tesla C1060, Tesla C2050, Thesis

May 21, 2013 by hgpu

Implementing Continuous Integration Software in an Established Computational Chemistry Software Package

Robin M. Betz, Ross C. Walker

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Tags: Benchmarking, Chemistry, Computational chemistry, CUDA, Molecular dynamics, nVidia, Software Engineering, Tesla M2090

May 21, 2013 by hgpu

An Investigation of the Performance Portability of OpenCL

S.J. Pennycook, S.D. Hammond, S.A. Wright, J.A. Herdman, I. Miller, S.A. Jarvis

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Tags: ATI, ATI FirePro V7800, Benchmarking, Computer science, CUDA, Fortran, MPI, nVidia, OpenCL, Package, Performance, Tesla C1060, Tesla C2050

May 21, 2013 by hgpu

Valar: A Benchmark Suite to Study the Dynamic Behavior of Heterogeneous Systems

Perhaad Mistry, Yash Ukidave, Dana Schaa, David Kaeli

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Tags: APU, ATI, ATI Radeon HD 7850, ATI Radeon HD 7970, Benchmarking, Computer science, Computer vision, Heterogeneous systems, OpenCL, Performance

April 22, 2013 by hgpu

Zero-copy I/O processing for low-latency GPU computing

Shinpei Kato, Jason Aumiller, Scott Brandt

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Tags: Algorithms, Benchmarking, CUDA, Data parallelism, nVidia, Plasma physics

April 16, 2013 by hgpu

Improving Performance Portability in OpenCL Programs

Yao Zhang, Mark Sinclair II, Andrew A. Chien

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Tags: APU, ATI, Benchmarking, Computer science, FFT, nVidia, OpenCL, Tesla C2050

March 26, 2013 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

Benchmarking Intel Xeon Phi to Guide Kernel Design

Comparative study of parallel programming models for multicore computing

Towards Rapid Prototyping of Parallel and HPC Applications (GPU Focus)

GPUburn: A System to Test and Mitigate GPU Hardware Failures

Performance Tradeoff Spectrum of Integer and Floating Point Applications

Composing multiple StarPU applications over heterogeneous machines: a supervised approach

Evaluating the Performance of Legacy Applications on Emerging Parallel Architectures

Implementing Continuous Integration Software in an Established Computational Chemistry Software Package

An Investigation of the Performance Portability of OpenCL

Valar: A Benchmark Suite to Study the Dynamic Behavior of Heterogeneous Systems

Zero-copy I/O processing for low-latency GPU computing

Improving Performance Portability in OpenCL Programs

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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