high performance computing on graphics processing units: hgpu.org

James Bergstra, Frederic Bastien, Olivier Breuleux, Pascal Lamblin, Razvan Pascanu, Olivier Delalleau, Guillaume Desjardins, David Warde-Farley, Ian Goodfellow, Arnaud Bergeron, Yoshua Bengio

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Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Package, Python

January 16, 2012 by hgpu

Declarative Parallel Programming for GPUs

Eric Holk, William Byrd, Nilesh Mahajan, Jeremiah Willcock, Arun Chauhan, Andrew Lumsdaine

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Tags: ATI, ATI Radeon HD 5770, Compilers, Computer science, nVidia, OpenCL

January 15, 2012 by hgpu

Extending a C-like Language for Portable SIMD Programming

Roland Leissa, Sebastian Hack, Ingo Wald

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Tags: Compilers, Computer science, High-level Languages, Intel, Performance

January 4, 2012 by hgpu

Toolchain for programming, simulating and studying the XMT many-core architecture

Fuat Keceli, Alexandros Tzannes, George C. Caragea, Rajeev Barua, Uzi Vishkin

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Tags: Algorithms, Compilers, Computer science, Hardware Architecture, nVidia, nVidia GeForce GTX 280, Package

December 24, 2011 by hgpu

Experiences Developing the OpenUH Compiler and Runtime Infrastructure

Barbara Chapman, Deepak Eachempati, Oscar Hernandez

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Tags: Code generation, Compilers, Computer science, nVidia, Package, PTX

December 19, 2011 by hgpu

Optimizing for a Many-Core Architecture without Compromising Ease-of-Programming

Uzi Vishkin, Rajeev Barua

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Tags: Algorithms, Benchmarking, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Optimization, Prefetch, Rendering, Thesis

December 16, 2011 by hgpu

Bringing Parallel Performance to Python with Domain-Specific Selective Embedded Just-in-Time Specialization

Shoaib Kamil, Derrick Coetzee, Armando Fox

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, Python

December 12, 2011 by hgpu

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

Speculative Parallelization on GPGPUs

Introducing ‘Bones’: A Parallelizing Source-to-Source Compiler Based on Algorithmic Skeletons

SPIRE, a Sequential to Parallel Intermediate Representation Extension

Decompilation of LLVM IR

Closing the Ninja Performance Gap through Traditional Programming and Compiler Technology

Theano: Deep Learning on GPUs with Python

Declarative Parallel Programming for GPUs

Extending a C-like Language for Portable SIMD Programming

Toolchain for programming, simulating and studying the XMT many-core architecture

Experiences Developing the OpenUH Compiler and Runtime Infrastructure

Optimizing for a Many-Core Architecture without Compromising Ease-of-Programming

Bringing Parallel Performance to Python with Domain-Specific Selective Embedded Just-in-Time Specialization

Recent source codes

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

SUperman: Highly Efficient Permanent Computation Library

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

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