high performance computing on graphics processing units: hgpu.org

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Automatic Test Case Reduction for OpenCL

Moritz Pflanzer, Alastair F. Donaldson, Andrei Lascu

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Tags: Code generation, Compilers, Computer science, nVidia, nVidia GeForce GTX Titan, OpenCL

May 3, 2016 by hgpu

Array Program Transformation with Loo.py by Example: High-Order Finite Elements

Andreas Klockner, Lucas C. Wilcox, T. Warburton

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Tags: Algorithms, AMD Radeon R9 Fury, ATI, Code generation, Computer science, Fortran, Numerical Analysis, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Performance, Prefetch, Programming Languages, Python, Tesla K40

April 29, 2016 by hgpu

Automatic Parallelization: Executing Sequential Programs on a Task-Based Parallel Runtime

Alcides Fonseca, Bruno Cabral, Joao Rafael, Ivo Correia

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Tags: Computer science, Java, OpenCL, Package, Programming Languages

April 29, 2016 by hgpu

To Co-Run, or Not To Co-Run: A Performance Study on Integrated Architectures

Feng Zhang, Jidong Zhai, Wenguang Chen, Bingsheng He, Shuhao Zhang

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Tags: Benchmarking, Computer science, OpenCL, Package

April 26, 2016 by hgpu

GPL: A GPU-based Pipelined Query Processing Engine

Johns Paul, Jiong He, Bingsheng He

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Tags: Analytical model, Computer science, Databases, nVidia, OpenCL

April 24, 2016 by hgpu

OpenCL-Based Mobile GPGPU Benchmarking: Methods and Challenges

Rotem Aviv, Guohui Wang

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Tags: Benchmarking, Mobile GPGPU, OpenCL

April 22, 2016 by lanshan317

Parallel Programming Models for Dense Linear Algebra on Heterogeneous Systems

M. Abalenkovs, A. Abdelfattah, J. Dongarra, M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, I. Yamazaki, A. YarKhan

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, OpenCL, Programming techniques, Review, Tesla K40

April 19, 2016 by hgpu

A Unified, Hardware-Fitted, Cross-GPU Performance Model

James Stevens, Andreas Klockner

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Tags: AMD Radeon R9 Fury, ATI, Computer science, nVidia, nVidia GeForce GTX Titan X, OpenCL, Performance, Tesla C2070, Tesla K40

April 19, 2016 by hgpu

Efficiency of general Krylov methods on GPUs – An experimental study

Hartwig Anzt, Jack Dongarra, Moritz Kreutzer, Gerhard Wellein, Martin Kohler

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Tags: Computer science, CUDA, Intel Xeon Phi, Linear Algebra, nVidia, OpenCL, Package, Sparse matrix, Tesla K40

April 16, 2016 by hgpu

pocl: A Performance-Portable OpenCL Implementation

Pekka Jaaskelainen, Carlos Sanchez de La Lama, Erik Schnetter, Kalle Raiskila, Jarmo Takala, Heikki Berg

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Tags: ARM, Computer science, Data parallelism, Heterogeneous systems, LLVM, OpenCL, performance portability

April 16, 2016 by hgpu

Parallel data mining algorithms for multi-dimensional points on GPUs

Takazumi Matsumoto

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Tags: Algorithms, Clustering, Computer science, Data mining, Heterogeneous systems, Nearest neighbour, nVidia, nVidia GeForce GTX 780, OpenCL, Thesis

April 16, 2016 by hgpu

Efficient Parallel Implementation for Single Block Orthogonal Dictionary Learning

Paul Irofti

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Tags: ATI, ATI FirePro V8800, Computer science, Machine learning, OpenCL

April 12, 2016 by hgpu

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

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high performance computing on graphics processing units: hgpu.org

Automatic Test Case Reduction for OpenCL

Array Program Transformation with Loo.py by Example: High-Order Finite Elements

Automatic Parallelization: Executing Sequential Programs on a Task-Based Parallel Runtime

To Co-Run, or Not To Co-Run: A Performance Study on Integrated Architectures

GPL: A GPU-based Pipelined Query Processing Engine

OpenCL-Based Mobile GPGPU Benchmarking: Methods and Challenges

Parallel Programming Models for Dense Linear Algebra on Heterogeneous Systems

A Unified, Hardware-Fitted, Cross-GPU Performance Model

Efficiency of general Krylov methods on GPUs – An experimental study

pocl: A Performance-Portable OpenCL Implementation

Parallel data mining algorithms for multi-dimensional points on GPUs

Efficient Parallel Implementation for Single Block Orthogonal Dictionary Learning

Recent source codes

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Celerity Runtime: High-level C++ for Accelerator Clusters

wgpy: WebGL accelerated numpy-compatible array library for web browser

Microbenchmarking OpenMP target offload with Catch2

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