high performance computing on graphics processing units: hgpu.org

Emanouil Atanassov, Michaela Barth, Mikko Byckling, Vali Codreanu, Nevena Ilieva, Tomas Karasek, Jorge Rodriguez, Sami Saarinen, Ole Widar Saastad, Michael Schliephake, Martin Stachon, Janko Strassburg, Volker Weinberg (Editor)

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

February 14, 2017 by hgpu

Machines and Algorithms

Peter A Boyle

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Tags: Algorithms, Computational Physics, CUDA, HEP, High Energy Physics - Lattice, Intel Xeon Phi, nVidia, Physics, QCD, Review

February 7, 2017 by hgpu

Analysis and implementation of a BLAST-Like algorithm for MIC architectures

Felipe Sulser Larraz

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Tags: Benchmarking, Bioinformatics, Biology, Computer science, Databases, Filtering, Intel Xeon Phi, Sequence alignment, Smith-Waterman algorithm, Thesis

February 2, 2017 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

Load Balancing for Constraint Solving with GPUs

Pipelined MapReduce: A Decoupled MapReduce RunTime for Shared Memory Multi-Processors

Exploiting Multi-level Parallelism on a Many-core System for the Application of Hyperheuristics to a Molecular Docking Problem

Optimization of Lattice Boltzmann Simulations on Heterogeneous Computers

Achieving high-performance with a sparse direct solver on Intel KNL

CHAOS: A Parallelization Scheme for Training Convolutional Neural Networks on Intel Xeon Phi

First Experiences Optimizing Smith-Waterman on Intel’s Knights Landing Processor

MCBooster: a library for fast Monte Carlo generation of phase-space decays on massively parallel platforms

LAMMPS’ PPPM Long-Range Solver for the Second Generation Xeon Phi

Best Practice Guide Intel Xeon Phi v2.0

Machines and Algorithms

Analysis and implementation of a BLAST-Like algorithm for MIC architectures

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