high performance computing on graphics processing units: hgpu.org

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Unlocking Bandwidth for GPUs in CC-NUMA Systems

Neha Agarwal, David Nellans, Mike O'Connor, Stephen W. Keckler, Thomas F. Wenisch

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Prefetch

February 6, 2015 by hgpu

Nucleation Studies on Graphics Processing Units

Benjamin J. Block

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Tags: Anisotropy, ATI, ATI Radeon HD 6970, Biology, Chemistry, Differential equations, Ising model, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 690, nVidia GeForce GTX Titan, OpenCL, Physics, Tesla K20, Thesis

February 6, 2015 by hgpu

GPGPU and MIC in Accelerated Cluster for Remote Sensed Image Processing Software

Olivier MELET, Toon Huysmans, Michel Hummel, Pierre-Marie Brunet

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Tags: CUDA, Image processing, Intel Xeon Phi, nVidia, nVidia GeForce GTX 480, OpenCL, Tesla K20

February 3, 2015 by hgpu

Mascar: Speeding up GPU Warps by Reducing Memory Pitstops

Ankit Sethia, D. Anoushe Jamshidi, Scott Mahlke

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Tags: Computer science, GPGPU-sim, Hardware Architecture, nVidia, nVidia GeForce GTX 480

February 1, 2015 by hgpu

Different Optimization Strategies and Performance Evaluation of Reduction on Multicore CUDA Architecture

Chhaya Patel

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Performance

January 30, 2015 by hgpu

GPU computing architecture for irregular parallelism

Wilson Wai Lun Fung

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Performance, Thesis

January 26, 2015 by hgpu

Can Portability Improve Performance? An Empirical Study of Parallel Graph Analytics

Ana Lucia Varbanescu, Merijn Verstraaten, Cees de Laat, Ate Penders, Alexandru Iosup, Henk Sips

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Tags: Algorithms, Computer science, Graph theory, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Tesla C2050

January 23, 2015 by hgpu

A New Sparse Matrix Vector Multiplication GPU Algorithm Designed for Finite Element Problems

Jonathan Wong, Ellen Kuhl, Eric Darve

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 480, Sparse matrix

January 5, 2015 by hgpu

Subdivision Surface Evaluation as Sparse Matrix-Vector Multiplication

Michael Driscoll

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Source codes

Tags: 3D Graphics and Realism, Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Sparse matrix

January 5, 2015 by hgpu

Real-Time Incompressible Fluid Simulation on the GPU

Xiao Nie, Leiting Chen, Tao Xiang

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Tags: 3D Graphics and Realism, CUDA, Fluid dynamics, Fluid simulation, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 780, Real-time graphics, Sorting

January 2, 2015 by hgpu

A Domain-specific Language to Facilitate Software Defined Radio Parallel Executable Patterns Deployment on Heterogeneous Architectures

Lerato J. Mohapi, Simon Winberg, Michael Inggs

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Tags: Algorithms, CUDA, DSP, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL, Signal processing

December 22, 2014 by hgpu

GPGPU-Sim

Filip Andersson

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Tesla C2050, Thesis

December 22, 2014 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

Unlocking Bandwidth for GPUs in CC-NUMA Systems

Nucleation Studies on Graphics Processing Units

GPGPU and MIC in Accelerated Cluster for Remote Sensed Image Processing Software

Mascar: Speeding up GPU Warps by Reducing Memory Pitstops

Different Optimization Strategies and Performance Evaluation of Reduction on Multicore CUDA Architecture

GPU computing architecture for irregular parallelism

Can Portability Improve Performance? An Empirical Study of Parallel Graph Analytics

A New Sparse Matrix Vector Multiplication GPU Algorithm Designed for Finite Element Problems

Subdivision Surface Evaluation as Sparse Matrix-Vector Multiplication

Real-Time Incompressible Fluid Simulation on the GPU

A Domain-specific Language to Facilitate Software Defined Radio Parallel Executable Patterns Deployment on Heterogeneous Architectures

GPGPU-Sim

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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