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GPU parallel computing: Programming language, debugging tools and data structures

Kun Zhou

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Tags: Algorithms, Computer science, CUDA, nVidia, Programming Languages

April 14, 2012 by hgpu

Verifying GPU Kernels by Test Amplification

Alan Leung, Manish Gupta, Yuvraj Agarwal, Rajesh Gupta, Ranjit Jhala

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Tags: Computer science, CUDA, nVidia, Programming Languages, Software Engineering

April 12, 2012 by hgpu

Nested Data-Parallelism on the GPU

Lars Bergstrom, John Reppy

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Source codes

Tags: Algorithms, Compilers, Computer science, CUDA, Data parallelism, nVidia, Package, Programming Languages, Tesla C2050

March 31, 2012 by hgpu

Enabling Fast, Noncontiguous GPU Data Movement in Hybrid MPI+GPU Environments

John Jenkins, Pavan Balaji, James Dinan, Nagiza F. Samatova, Rajeev Thakur

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Tags: Computer science, CUDA, MPI, nVidia, Performance, Programming Languages, Programming techniques, Tesla C2050

March 18, 2012 by hgpu

Chestnut: A GPU Programming Language for Non-Experts

Andrew Stromme, Ryan Carlson, Tia Newhall

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Programming Languages

March 1, 2012 by hgpu

Task Parallelism and Synchronization: An Overview of Explicit Parallel Programming Languages

Dounia Khaldi, Pierre Jouvelot, Corinne Ancourt, Francois Irigoin

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Tags: Computer science, OpenCL, Overview, Programming Languages

February 11, 2012 by hgpu

Building-Blocks for Performance Oriented DSLs

Tiark Rompf, Arvind K. Sujeeth, HyoukJoong Lee, Kevin J. Brown, Hassan Chafi, Martin Odersky, Kunle Olukotun

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Programming Languages, Tesla C2050

November 23, 2011 by hgpu

Programming Future Parallel Architectures with Haskell and Intel ArBB

Bo Joel Svensson, Ryan Newton

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Performance, Programming Languages

November 17, 2011 by hgpu

Characterization and Transformation of Unstructured Control Flow in GPU Applications

Haicheng Wu, Gregory Diamos, Si Li, Sudhakar Yalamanchili

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Performance, Programming Languages

November 17, 2011 by hgpu

MELT-a Translated Domain Specific Language Embedded in the GCC Compiler

Basile Starynkevitch

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Tags: Compilers, Computer science, OpenCL, Optimization, Programming Languages, Software Engineering

November 7, 2011 by hgpu

Functional Programming for High-Performance Computing on Heterogeneous Architectures

Sylvain Henry

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro FX 5800, OpenCL, Optimization, Performance, Programming Languages, Programming techniques

November 7, 2011 by hgpu

SIMD Re-Convergence At Thread Frontiers

Gregory Diamos, Andrew Kerr, Haicheng Wu, Sudhakar Yalamanchili, Benjamin Ashbaugh, Subramaniam Maiyuran

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Tags: Computer science, CUDA, nVidia, Performance, Programming Languages, PTX

October 31, 2011 by hgpu

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

GPU parallel computing: Programming language, debugging tools and data structures

Verifying GPU Kernels by Test Amplification

Nested Data-Parallelism on the GPU

Enabling Fast, Noncontiguous GPU Data Movement in Hybrid MPI+GPU Environments

Chestnut: A GPU Programming Language for Non-Experts

Task Parallelism and Synchronization: An Overview of Explicit Parallel Programming Languages

Building-Blocks for Performance Oriented DSLs

Programming Future Parallel Architectures with Haskell and Intel ArBB

Characterization and Transformation of Unstructured Control Flow in GPU Applications

MELT-a Translated Domain Specific Language Embedded in the GCC Compiler

Functional Programming for High-Performance Computing on Heterogeneous Architectures

SIMD Re-Convergence At Thread Frontiers

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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