high performance computing on graphics processing units: hgpu.org

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Parallel Spherical Harmonic Transforms on heterogeneous architectures (GPUs/multi-core CPUs)

Mikolaj Szydlarski, Pierre Esterie, Joel Falcou, Laura Grigori, Radek Stompor

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Tags: Algorithms, Astrophysics, Cluster computing, Computational Physics, Cosmology, Cosmology and Extragalactic Astrophysics, CUDA, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 480, Tesla S1070

June 6, 2012 by hgpu

A new parallelisation technique for heterogeneous CPUs

Youssef Omran Gdura

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Tags: Benchmarking, Code generation, Computer science, Heterogeneous systems, Programming techniques, Thesis

June 5, 2012 by hgpu

Hierarchical Partitioning Algorithm for Scientific Computing on Highly Heterogeneous CPU + GPU Clusters

David Clarke, Aleksandar Ilic, Alexey Lastovetsky, Leonel Sousa

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Tags: Computer science, CPU cluster, GPU cluster, Heterogeneous systems, Matrix multiplication, nVidia, Tesla C2050, Tesla T10

June 5, 2012 by hgpu

A Compiler and Runtime for Heterogeneous Computing

Joshua Auerbach, David F. Bacon, Ioana Burcea, Perry Cheng, Stephen J. Fink, Rodric Rabbah, Sunil Shukla

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Tags: Computer science, FPGA, Heterogeneous systems, Java, nVidia, nVidia GeForce GTX 580, OpenCL, Programming Languages

June 4, 2012 by hgpu

Pipelining the Fast Multipole Method over a Runtime System

Emmanuel Agullo, Beranger Bramas, Olivier Coulaud, Eric Darve, Matthias Messner, Takahashi Toru

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Tags: Algorithms, Computer science, Fast multipole method, Heterogeneous systems, nVidia, Physics, Tesla M2070, Tesla M2090

June 4, 2012 by hgpu

clSpMV: A Cross-Platform OpenCL SpMV Framework on GPUs

Bor-Yiing Su, Kurt Keutzer

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Tags: ATI, ATI Radeon HD 6970, Computer science, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Sparse matrix

May 30, 2012 by hgpu

Accelerating an imaging spectroscopy algorithm for submerged marine environments using heterogeneous computing

Matthew Sellitto

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Tags: Algorithms, Heterogeneous systems, Image processing, nVidia, OpenCL, Optimization, Sensing, Tesla M2070, Thesis

May 30, 2012 by hgpu

Compiler optimizations for directive-based programming for accelerators

Matias Piispanen

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, OpenCL, Optimization

May 24, 2012 by hgpu

High-Level Support for Pipeline Parallelism on Many-Core Architectures

Siegfried Benkner, Enes Bajrovic, Erich Marth, Martin Sandrieser, Raymond Namyst, Samuel Thibault

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480

May 20, 2012 by hgpu

Automatic Implementation of Evolutionary Algorithms on GPUs using ESDL

Steve Dower

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Tags: Algorithms, Computer science, Evolutionary Computations, Heterogeneous systems, nVidia, nVidia GeForce GT 540 M

May 19, 2012 by hgpu

C-DAC’s Efforts – Application Kernels on HPC Cluster with GPU Accelerators

VCV.Rao, Nisha Agrawa, Samrit Maity

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Tags: AMD FirePro V5900, AMD FirePro V7900, AMD FireStream 9350, ATI, Computer science, CUDA, Differential equations, FEM, Finite difference, Finite element method, GPU cluster, Heterogeneous systems, Linear Algebra, MPI, nVidia, OpenCL, Partial differential equations, PDEs, Tesla C2060

May 19, 2012 by hgpu

Programming and Scheduling Model for Supporting Heterogeneous Accelerators in Linux

Tobias Beisel, Tobias Wiersema, Christian Plessl, Andre Brinkmann

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Operating systems, Package, Task scheduling

May 19, 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

Parallel Spherical Harmonic Transforms on heterogeneous architectures (GPUs/multi-core CPUs)

A new parallelisation technique for heterogeneous CPUs

Hierarchical Partitioning Algorithm for Scientific Computing on Highly Heterogeneous CPU + GPU Clusters

A Compiler and Runtime for Heterogeneous Computing

Pipelining the Fast Multipole Method over a Runtime System

clSpMV: A Cross-Platform OpenCL SpMV Framework on GPUs

Accelerating an imaging spectroscopy algorithm for submerged marine environments using heterogeneous computing

Compiler optimizations for directive-based programming for accelerators

High-Level Support for Pipeline Parallelism on Many-Core Architectures

Automatic Implementation of Evolutionary Algorithms on GPUs using ESDL

C-DAC’s Efforts – Application Kernels on HPC Cluster with GPU Accelerators

Programming and Scheduling Model for Supporting Heterogeneous Accelerators in Linux

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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