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Analysis and Optimization Techniques for Massively Parallel Processors

Wenhao Jia

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, PTX, Tesla C2070, Thesis, Virtualization

December 15, 2014 by hgpu

StreamWorks: An Energy-efficient Embedded Co-processor for Stream Computing

Amrit Panda

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Tags: Computer science, CUDA, nVidia, Tesla K20, Thesis, Virtualization

October 18, 2014 by hgpu

A Complete and Efficient CUDA-Sharing Solution for HPC Clusters

Antonio J. Pena, Carlos Reano, Federico Silla, Rafael Mayo, Enrique S. Quintana-Orti, Jose Duato

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Tags: Computer science, CUDA, GPU cluster, nVidia, Tesla K20, Virtualization

October 14, 2014 by hgpu

GPU Virtualization for High Performance General Purpose Computing on the ESX Hypervisor

Lan Vu, Hari Sivaraman, Rishi Bidarkar

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Tags: Computer science, CUDA, nVidia, nVidia Quadro 4000, Virtualization

August 23, 2014 by hgpu

GPUvm: Why Not Virtualizing GPUs at the Hypervisor?

Yusuke Suzuki, Shinpei Kato, Hiroshi Yamada, Kenji Kono

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Tags: Cloud, Computer science, CUDA, nVidia, nVidia Quadro 6000, Operating systems, Virtualization

July 4, 2014 by hgpu

Enabling High Performance Computing in Cloud Infrastructure using rCUDA

Yousuf Sait I, Vijayalakshmi R

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Tags: Cloud, Computer science, CUDA, nVidia, Tesla C2075, Tesla K20, Virtualization

June 11, 2014 by hgpu

Evaluating GPU Passthrough in Xen for High Performance Cloud Computing

Andrew J. Younge, John Paul Walters, Stephen Crago, Geoffrey C. Fox

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Tags: Cloud, Computer science, CUDA, nVidia, Tesla C2075, Tesla K20, Virtualization

June 1, 2014 by hgpu

GPU Passthrough Performance: A Comparison of KVM, Xen, VMWare ESXi, and LXC for CUDA and OpenCL Applications

John Paul Walters, Andrew J. Younge, Dong-In Kang, Ke-Thia Yao, Mikyung Kang, Stephen P. Crago, Geoffrey C. Fox

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Tags: Cloud, Computer science, CUDA, nVidia, OpenCL, Tesla C2075, Tesla K20, Virtualization

May 26, 2014 by hgpu

On the Use of Remote GPUs and Low-Power Processors for the Acceleration of Scientific Applications

A. Castello, J. Duato, R. Mayo, A. J. Pena, E. S. Quintana-Orti, V. Roca, F. Silla

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Tags: Bioinformatics, Computer science, CUDA, Energy-efficient computing, Heterogeneous systems, Molecular dynamics, nVidia, nVidia GeForce GTX 480, Virtualization

April 27, 2014 by hgpu

Confidentiality Issues on a GPU in a Virtualized Environment

Clementine Maurice, Christoph Neumann, Olivier Heen, Aurelien Francillon

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Tags: Cloud, Computer science, CUDA, nVidia, Security, Tesla K20, Virtualization

February 11, 2014 by hgpu

Enabling High Performance Computing in Cloud Infrastructure using Virtualized GPUs

Andrew J. Younge, John Paul Walters, Steve Crago, Geoffrey C. Fox

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Tags: Cloud, Computer science, CUDA, nVidia, Tesla C2075, Tesla K20, Virtualization

December 23, 2013 by hgpu

LoGV: Low-overhead GPGPU Virtualization

Mathias Gottschlag, Marius Hillenbrand, Jens Kehne, Jan Stoess, Frank Bellosa

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Tags: Cloud, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Virtualization

November 23, 2013 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

Analysis and Optimization Techniques for Massively Parallel Processors

StreamWorks: An Energy-efficient Embedded Co-processor for Stream Computing

A Complete and Efficient CUDA-Sharing Solution for HPC Clusters

GPU Virtualization for High Performance General Purpose Computing on the ESX Hypervisor

On the Use of Remote GPUs and Low-Power Processors for the Acceleration of Scientific Applications

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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