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File I/O on Intel Xeon Phi Coprocessors: RAM disks, VirtIO, NFS and Lustre

Andrey Vladimirov, Vadim Karpusenko, Tony Yoo

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Tags: Benchmarking, Computer science, I/O, Intel Xeon Phi, Portability, Xeon Phi

July 29, 2014 by Andrey Vladimirov

A Similarity-Based Analysis Tool for Scientific Application Porting

Wei Ding

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Tags: Benchmarking, Computer science, CUDA, MPI, nVidia, OpenMP, Performance, Portability, Tesla C2070, Thesis

February 17, 2014 by hgpu

Designing Bit-Reproducible Portable High-Performance Applications

Andrea Arteaga, Oliver Fuhrer, Torsten Hoefler

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, MPI, nVidia, Portability, Tesla K20

February 12, 2014 by hgpu

Heterogeneous Clustering with Homogeneous Code: Accelerate MPI Applications Without Code Surgery Using Intel Xeon Phi Coprocessors

Andrey Vladimirov and Vadim Karpusenko

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Tags: Heterogeneous systems, Intel Phi, Intel Xeon Phi, Monte Carlo simulation, MPI, Portability, Task scheduling

October 18, 2013 by Andrey Vladimirov

One OpenCL to Rule Them All?

Romain Dolbeau, Francois Bodin, Guillaume Colin de Verdiere

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Tags: ATI, ATI Radeon HD 7970, Computer science, Intel, Intel Phi, nVidia, OpenACC, OpenCL, Performance, Portability, Tesla K20

April 21, 2013 by hgpu

How to Benefit from AMD, Intel and Nvidia Accelerator Technologies in Scilab

Thibault Person, Francois Bodin

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Source codes

Tags: ATI, ATI Radeon HD 7970, Computer science, CUDA, Intel, Intel Phi, nVidia, OpenCL, Package, Performance, Portability, Tesla K20

March 24, 2013 by hgpu

KERNELGEN – A Toolchain for Automatic GPU-centric Applications Porting

Dmitry Mikushin, Nicolas Likhogrud

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Source codes

Tags: Computer science, CUDA, nVidia, OpenCL, Package, Portability, Tesla C2050

October 3, 2012 by hgpu

Adaptive Input-aware Compilation for Graphics Engines

Mehrzad Samadi, Amir Hormati, Mojtaba Mehrara, Janghaeng Lee, and Scott Mahlke

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Tags: Compiler, CUDA, GPU, nVidia, nVidia GeForce GTX 285, Optimization, Portability, Streaming, Tesla C2050

March 31, 2012 by Moaddeli

GPU-Smash: Compression abstraction library

A Parallel Compression Pipeline for Improving GPU Virtualization Data Transfers

Owl: Differential-based Side-Channel Leakage Detection for CUDA Applications

pSTL-Bench: Micro-benchmark suite designed to evaluate the scalability and efficiency of parallel C++ STL implementations

Exploring Scalability in C++ Parallel STL Implementations

Noarr Structures

Abstractions for C++ code optimizations in parallel high-performance applications

$3D-fractal-generators$

HiCCL: A hierarchical collective communications library with portable optimizations

HiCCL: A Hierarchical Collective Communication Library

GRAFX: An Open-Source Library for Audio Processing Graphs in PyTorch

In-browser Inference Measurement

Anatomizing Deep Learning Inference in Web Browsers

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high performance computing on graphics processing units: hgpu.org

File I/O on Intel Xeon Phi Coprocessors: RAM disks, VirtIO, NFS and Lustre

A Similarity-Based Analysis Tool for Scientific Application Porting

Designing Bit-Reproducible Portable High-Performance Applications

Heterogeneous Clustering with Homogeneous Code: Accelerate MPI Applications Without Code Surgery Using Intel Xeon Phi Coprocessors

One OpenCL to Rule Them All?

How to Benefit from AMD, Intel and Nvidia Accelerator Technologies in Scilab

KERNELGEN – A Toolchain for Automatic GPU-centric Applications Porting

Adaptive Input-aware Compilation for Graphics Engines

Recent source codes

GPU-Smash: Compression abstraction library

Owl: Differential-based Side-Channel Leakage Detection for CUDA Applications

pSTL-Bench: Micro-benchmark suite designed to evaluate the scalability and efficiency of parallel C++ STL implementations

Noarr Structures

3D-fractal-generators

SyncPerformance

VerCors: a verification toolset for verifying parallel and concurrent software

HiCCL: A hierarchical collective communications library with portable optimizations

GRAFX: An Open-Source Library for Audio Processing Graphs in PyTorch

In-browser Inference Measurement

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