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HyPHI – task based hybrid execution C++ library for the Intel Xeon Phi coprocessor

Jiri Dokulil, Enes Bajrovic, Siegfried Benkner, Martin Sandrieser, Beverly Bachmayer

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Tags: Computer science, Intel Phi, Intel Xeon Phi

November 20, 2013 by hgpu

Anatomy of High-Performance Many-Threaded Matrix Multiplication

Tyler M. Smith, Robert van de Geijn, Mikhail Smelyanskiy, Jeff R. Hammond, Field Van Zee

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Tags: Computer science, Intel Phi, Intel Xeon Phi, Matrix multiplication, Performance

November 13, 2013 by hgpu

Performance Evaluation of R with Intel Xeon Phi Coprocessor

Yaakoub El-Khamra, Niall Gaffney, David Walling, Eric Wernert, Weijia Xu, Hui Zhang

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Tags: Computer science, CUDA, CULA, High-level Languages, Intel Phi, Intel Xeon Phi, nVidia, Package, Performance, Tesla K20

November 12, 2013 by hgpu

Preliminary Experiments with XKaapi on Intel Xeon Phi Coprocessor

Joao Vicente Ferreira Lima, Francois Broquedis, Thierry Gautier, Bruno Raffin

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Tags: Computer science, Factorization, Intel, Intel Phi, Intel Xeon Phi

November 11, 2013 by hgpu

Explorations of the Viability of ARM and Xeon Phi for Physics Processing

David Abdurachmanov, Kapil Arya, Josh Bendavid, Tommaso Boccali, Gene Cooperman, Andrea Dotti, Peter Elmer, Giulio Eulisse, Francesco Giacomini, Christopher D. Jones, Matteo Manzali, Shahzad Muzaffar

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Tags: ARM, Computational Physics, High Energy Physics - Experiment, Intel Phi, Intel Xeon Phi, Performance, Physics

November 11, 2013 by hgpu

Many-core applications to online track reconstruction in HEP experiments

S. Amerio, D. Bastieri, M. Corvo, A. Gianelle, W. Ketchum, T. Liu, A. Lonardo, D. Lucchesi, S. Poprocki, R. Rivera, L. Tosoratto, P. Vicini, P. Wittich

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Tags: CUDA, High Energy Physics - Experiment, Intel Phi, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan, Physics, Tesla K20, Tesla M2050

November 6, 2013 by hgpu

Comparative Performance Analysis of Intel Xeon Phi, GPU, and CPU

George Teodoro, Tahsin Kurc, Jun Kong, Lee Cooper, Joel Saltz

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Tags: Computer science, CUDA, Intel Phi, Intel Xeon Phi, Microscopy, nVidia, OpenMP, Performance, Task scheduling, Tesla K20

November 6, 2013 by hgpu

Performance of Kepler GTX Titan GPUs and Xeon Phi System

Hwancheol Jeong, Weonjong Lee, Jeonghwan Pak, Kwang-jong Choi, Sang-Hyun Park, Jun-sik Yoo, Joo Hwan Kim, Joungjin Lee, Young Woo Lee

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Tags: Computational Physics, CUDA, Intel Phi, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan, Performance, Physics, Tesla K20

November 6, 2013 by hgpu

Use of Checkpoint-Restart for Complex HEP Software on Traditional Architectures and Intel MIC

Kapil Arya, Gene Cooperman, Andrea Dotti, Peter Elmer

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Tags: Computational Physics, High Energy Physics - Experiment, Intel Phi, Intel Xeon Phi, Numerical Analysis, Physics

November 4, 2013 by hgpu

First Evaluation of the CPU, GPGPU and MIC Architectures for Real Time Particle Tracking based on Hough Transform at the LHC

V. Halyo, P. LeGresley, P. Lujan, V. Karpusenko, A. Vladimirov

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Tags: Algorithms, Computational Physics, CUDA, High Energy Physics - Experiment, Intel Phi, Intel Xeon Phi, nVidia, Physics, Tesla K20

October 29, 2013 by hgpu

An Empirical Study of Intel Xeon Phi

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

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

October 25, 2013 by hgpu

SIMD Parallel Gibbs Sampling of Probabilistic Directed Acyclic Graphs

Alireza S. Mahani, Mansour T.A. Sharabiani

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Tags: Artificial intelligence, Bayesian, Intel Phi, Intel Xeon Phi, OpenMP, Statistics

October 22, 2013 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 plugin for PySCF

Python-Based Quantum Chemistry Calculations with GPU Acceleration

QArray

QArray: a GPU-accelerated constant capacitance model simulator for large quantum dot arrays

Celerity: High-level C++ for Accelerator Clusters

Balancing Tracking Granularity and Parallelism in Many-Task Systems: The Horizons Approach

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

Parallel Gaussian process with kernel approximation in CUDA

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