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Lattice QCD on Intel Xeon Phi

Balint Joo, Dhiraj D. Kalamkar, Karthikeyan Vaidyanathan, Mikhail Smelyanskiy, Kiran Pamnany, Victor W Lee, Pradeep Dubey, William Watson III

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Tags: CUDA, High Energy Physics - Lattice, Intel, Intel Phi, nVidia, Physics, QCD, Tesla K20

July 20, 2013 by hgpu

Benchmarking Intel Xeon Phi to Guide Kernel Design

Jianbin Fang, Ana Lucia Varbanescu, Henk Sips, Lilun Zhang, Yonggang Che, Chuanfu Xu

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Tags: Benchmarking, Computer science, Intel, Intel Phi, Performance

July 14, 2013 by hgpu

Identifying the Key Features of Intel Xeon Phi: A Comparative Approach

Jianbin Fang, Ana Lucia Varbanescu, Henk Sips

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Tags: Computer science, Intel, Intel Phi, Performance

July 13, 2013 by hgpu

Preliminary Experiences with the Uintah Framework on Intel Xeon Phi and Stampede

Qingyu Meng, Alan Humphrey, John Schmidt, Martin Berzins

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Tags: Computer science, Heterogeneous systems, Intel, Intel Phi, Performance

July 2, 2013 by hgpu

Intel Xeon Phi Coprocessor High-Performance Programming

Jim Jeffers, James Jeffers, James Reinders

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Tags: Book, Computer science, Intel, Intel Phi, OpenMP, Package, Review

June 30, 2013 by hgpu

Best Practice Guide – Intel Xeon Phi

Michaela Barth, Mikko Byckling, Nevena Ilieva, Sami Saarinen, Michael Schliephake, Volker Weinberg

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Tags: Computer science, Intel, Intel Phi, OpenMP, Review

June 30, 2013 by hgpu

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

March 24, 2013 by hgpu

Offload Compiler Runtime for the Intel Xeon Phi Coprocessor

Chris J. Newburn, Rajiv Deodhar, Serguei Dmitriev, Ravi Murty, Ravi Narayanaswamy, John Wiegert, Francisco Chinchilla, Russell McGuire

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Tags: Compilers, Computer science, Heterogeneous systems, Intel, Intel Phi, Programming techniques

February 18, 2013 by hgpu

Exploring SIMD for Molecular Dynamics, Using Intel Xeon Processors and Intel Xeon Phi Coprocessors

S. J. Pennycook, C. J. Hughes, M. Smelyanskiy, S. A. Jarvis

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Tags: Algorithms, Benchmarking, Computer science, Intel, Intel Phi, Molecular dynamics

February 14, 2013 by hgpu

Performance Evaluation of Sparse Matrix Multiplication Kernels on Intel Xeon Phi

Erik Saule, Kamer Kaya, Umit V. Catalyurek

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Tags: Computer science, CUDA, Hardware Architecture, Intel, Intel Phi, Matrix multiplication, nVidia, Performance, Sparse matrix, Tesla C2050, Tesla K20

February 6, 2013 by hgpu

OpenMP Programming on Intel R Xeon Phi TM Coprocessors: An Early Performance Comparison

Tim Cramer, Dirk Schmidl, Michael Klemm, Dieter an Mey

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Tags: Benchmarking, Computer science, Intel, Intel Phi, OpenMP, Performance

December 8, 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

Lattice QCD on Intel Xeon Phi

Benchmarking Intel Xeon Phi to Guide Kernel Design

Identifying the Key Features of Intel Xeon Phi: A Comparative Approach

Preliminary Experiences with the Uintah Framework on Intel Xeon Phi and Stampede

Intel Xeon Phi Coprocessor High-Performance Programming

Best Practice Guide – Intel Xeon Phi

One OpenCL to Rule Them All?

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

Offload Compiler Runtime for the Intel Xeon Phi Coprocessor

Exploring SIMD for Molecular Dynamics, Using Intel Xeon Processors and Intel Xeon Phi Coprocessors

Performance Evaluation of Sparse Matrix Multiplication Kernels on Intel Xeon Phi

OpenMP Programming on Intel R Xeon Phi TM Coprocessors: An Early Performance Comparison

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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