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Hybrid CPU-GPU Distributed Framework for Large Scale Mobile Networks Simulation

Ben Romdhanne Bilel, Nikaein Navid, Mohamed Said Mosli Bouksiaa, Christian Bonnet

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Tags: Computer science, CUDA, Hybrid computing, nVidia, nVidia GeForce GTX 460, Programming techniques

February 3, 2013 by hgpu

OWL: Cooperative Thread Array Aware Scheduling Techniques for Improving GPGPU Performance

Adwait Jog, Onur Kayiran, Nachiappan Chidambaram Nachiappan, Asit K. Mishra, Mahmut T. Kandemir, Onur Mutlu, Ravishankar Iyer, Chita R. Das

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Performance, Prefetch, Programming techniques

January 31, 2013 by hgpu

Automatic Parallelization for GPUs

Thomas B. Jablin

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Programming techniques, Thesis

January 26, 2013 by hgpu

Performance comparison of gauss-Jordan elimination method using OpenMP and CUDA

Baha Sen, Nesrin Aydin Atasoy, Caner Ozcan

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 9500 GT, OpenMP, Performance, Programming techniques

January 7, 2013 by hgpu

Algorithmic Skeleton Framework for the Orchestration of GPU Computations

Ricardo Jorge dos Santos Marques

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 680, OpenCL, Optimization, Programming techniques, Tesla C2050

December 25, 2012 by hgpu

Productive High Performance Parallel Programming with Auto-tuned Domain-Specific Embedded Languages

Shoaib Ashraf Kamil

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Performance, Programming techniques, Thesis

December 16, 2012 by hgpu

Towards Building Error Resilient GPGPU Applications

Bo Fang, Jiesheng Wei, Karthik Pattabiraman, Matei Ripeanu

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Tags: Computer science, CUDA, nVidia, Programming techniques, Tesla C2075

December 8, 2012 by hgpu

Mapping Streaming Applications to OpenCL

Abhishek Ray

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Tags: ATI, ATI Radeon HD 6970, Computer science, nVidia, OpenCL, Programming techniques, Tesla C2050

December 5, 2012 by hgpu

Kite: Braided Parallelism for Heterogeneous Systems

J. Garrett Morris, Benedict R. Gaster, Lee Howes

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Tags: Compilers, Computer science, Heterogeneous systems, OpenCL, Programming techniques

November 5, 2012 by hgpu

A GPU Approach to Fortran Legacy Systems

Mariano Mendez, Fernando G. Tinetti

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Tags: Computer science, CUDA, Fortran, nVidia, OpenACC, Programming techniques, Tesla C2075

October 29, 2012 by hgpu

Enhancing Productivity and Performance Portability of General-Purpose Parallel Programming

Alexandros Tzannes

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Tags: Compilers, Computer science, Programming techniques, Thesis

October 17, 2012 by hgpu

Mesh Independent Loop Fusion for Unstructured Mesh Applications

Carlo Bertolli, Adam Betts, Gihan R. Mudalige, Paul H.J. Kelly, Michael B. Giles

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Tags: Computer science, CUDA, nVidia, Programming techniques, Tesla M2050

October 13, 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

Hybrid CPU-GPU Distributed Framework for Large Scale Mobile Networks Simulation

OWL: Cooperative Thread Array Aware Scheduling Techniques for Improving GPGPU Performance

Automatic Parallelization for GPUs

Performance comparison of gauss-Jordan elimination method using OpenMP and CUDA

Algorithmic Skeleton Framework for the Orchestration of GPU Computations

Productive High Performance Parallel Programming with Auto-tuned Domain-Specific Embedded Languages

Towards Building Error Resilient GPGPU Applications

Mapping Streaming Applications to OpenCL

Kite: Braided Parallelism for Heterogeneous Systems

A GPU Approach to Fortran Legacy Systems

Enhancing Productivity and Performance Portability of General-Purpose Parallel Programming

Mesh Independent Loop Fusion for Unstructured Mesh Applications

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

Most viewed papers (last 30 days)