high performance computing on graphics processing units: hgpu.org

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Enhancing GPU Parallelism in Nature-Inspired Algorithms

Jose M. Cecilia, Andy Nisbet, Martyn Amos, Jose M. Garcia, Manuel Ujaldon

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Tags: Algorithms, Computational modelling, Computer science, CUDA, Data parallelism, nVidia, Optimization, P systems, Tesla C1060, Tesla C2050

May 12, 2012 by hgpu

Efficient Parallelization of Natural Language Applications using GPUs

Chao-Yue Lai

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Tags: Algorithms, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Optimization, Thesis

May 11, 2012 by hgpu

Enhancing data parallelism for Ant Colony Optimization on GPUs

Jose M. Cecilia, Jose M. Garcia, Andy Nisbet, Martyn Amos, Manuel Ujaldon

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Tags: Algorithms, Computer science, CUDA, Data parallelism, nVidia, Optimization, Tesla C2050

May 10, 2012 by hgpu

Nested Data-Parallelism on the GPU

Lars Bergstrom, John Reppy

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

March 31, 2012 by hgpu

Accelerating the FDTD Method Using SSE and Graphics Processing Units

Matthew J. Livesey

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Tags: Computer science, CUDA, Data parallelism, FDTD, Finite-difference time-domain, nVidia, Tesla M2050, Tesla T10, Thesis

March 28, 2012 by hgpu

Improving Performance of OpenCL on CPUs

Ralf Karrenberg, Sebastian Hack

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Tags: Code generation, Computer science, Data parallelism, OpenCL, Performance

March 27, 2012 by hgpu

CUDA 2D Stencil Computations for the Jacobi Method

Jose Maria Cecilia, Jose Manuel Garcia, Manuel Ujaldon

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Differential equations, Linear Algebra, nVidia, Optimization, Tesla C1060, Tesla C870

March 16, 2012 by hgpu

Expressive Array Constructs in an Embedded GPU Kernel Programming Language

Koen Claessen, Mary Sheeran, Bo Joel Svensson

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Tags: Algorithms, Code generation, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Sorting

March 13, 2012 by hgpu

Synthesizing Software from a ForSyDe Model Targeting GPGPUs

Gabriel Hjort Blindell

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Tags: Computer science, CUDA, Data parallelism, nVidia, nVidia Quadro FX 600, nVidia Quadro NVS 290, Software Engineering, Thesis

March 6, 2012 by hgpu

GPGPU Processing in CUDA Architecture

Jayshree Ghorpade, Jitendra Parande, Madhura Kulkarni, Amit Bawaskar

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Tags: Computer science, CUDA, Data parallelism, DirectCompute, nVidia, OpenCL, Review

February 21, 2012 by hgpu

Work Stealing Inside GPUs

Julio Toss

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Tags: Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 280, Task scheduling, Tesla C2050, Thesis

February 13, 2012 by hgpu

Verifiable Computation with Massively Parallel Interactive Proofs

Justin Thaler, Mike Roberts, Michael Mitzenmacher, Hanspeter Pfister

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Tags: Benchmarking, Cloud, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 480, Package, Security

February 8, 2012 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

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

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

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Enhancing GPU Parallelism in Nature-Inspired Algorithms

Efficient Parallelization of Natural Language Applications using GPUs

Enhancing data parallelism for Ant Colony Optimization on GPUs

Nested Data-Parallelism on the GPU

Accelerating the FDTD Method Using SSE and Graphics Processing Units

Improving Performance of OpenCL on CPUs

CUDA 2D Stencil Computations for the Jacobi Method

Expressive Array Constructs in an Embedded GPU Kernel Programming Language

Synthesizing Software from a ForSyDe Model Targeting GPGPUs

GPGPU Processing in CUDA Architecture

Work Stealing Inside GPUs

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

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