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Lattice QCD simulations using the OpenACC platform

Pushan Majumdar

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Tags: CUDA, HEP, High Energy Physics - Lattice, nVidia, OpenACC, Physics, QCD, Tesla X2090

November 19, 2016 by hgpu

MILC staggered conjugate gradient performance on Intel KNL

Carleton DeTar, Douglas Doerfler, Steven Gottlieb, Ashish Jha, Dhiraj Kalamkar, Ruizi Li, Doug Toussaint

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Tags: Computational Physics, Data parallelism, High Energy Physics - Lattice, Intel Xeon Phi, MPI, OpenMP, Physics

November 3, 2016 by hgpu

Flux tubes at Finite Temperature

Pedro Bicudo, Nuno Cardoso, Marco Cardoso

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Tags: CUDA, High Energy Physics - Lattice, nVidia, Phase transition, Physics, QCD

August 31, 2016 by hgpu

An Optimized Multiple Right-Hand Side Dslash Kernel for Intel Xeon Phi

Aaron Walden

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Tags: High Energy Physics - Lattice, Intel Xeon Phi, Physics, QCD, Thesis

July 28, 2016 by hgpu

First Application of Lattice QCD to Pezy-SC Processor

Tatsumi Aoyama, Ken-Ichi Ishikawa, Yasuyuki Kimura, Hideo Matsufuru, Atsushi Sato, Tomohiro Suzuki, Sunao Torii

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Tags: High Energy Physics - Lattice, Matrix multiplication, OpenCL, Physics, QCD

June 14, 2016 by hgpu

Adaptive algebraic multigrid on SIMD architectures

Simon Heybrock, Matthias Rottmann, Peter Georg, Tilo Wettig

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Tags: Algorithms, Computational Physics, High Energy Physics - Lattice, Intel Xeon Phi, Physics

December 15, 2015 by hgpu

Accelerating Twisted Mass LQCD with QPhiX

Mario Schrock, Silvano Simula, Alexei Strelchenko

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Tags: High Energy Physics - Lattice, Intel Xeon Phi, Package, Physics, QCD

November 4, 2015 by hgpu

Overlap fermions on GPUs

Nigel Cundy, Weonjong Lee

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Tags: CUDA, High Energy Physics - Lattice, nVidia, nVidia GeForce GTX Titan, Physics

October 27, 2015 by hgpu

CPU and GPU Implementation of QCD by using OpenCL

J. Sa, B. Noh, H. Kim, D. Choi, S. Lee, Y. Chung, D. Kim, H. Jang

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Tags: High Energy Physics - Lattice, nVidia, nVidia GeForce GTX 550, OpenCL, Physics, QCD

June 30, 2015 by hgpu

Energy-and cost-efficient Lattice-QCD computations using graphics processing units

Matthias Bach

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Tags: Algorithms, AMD FirePro S10000, ATI, ATI Radeon HD 5870, ATI Radeon HD 7970, Energy-efficient computing, High Energy Physics - Lattice, OpenCL, Physics, QCD, Thesis

March 3, 2015 by hgpu

QPACE 2 and Domain Decomposition on the Intel Xeon Phi

Paul Arts, Jacques Bloch, Peter Georg, Benjamin Glaessle, Simon Heybrock, Yu Komatsubara, Robert Lohmayer, Simon Mages, Bernhard Mendl, Nils Meyer, Alessio Parcianello, Dirk Pleiter, Florian Rappl, Mauro Rossi, Stefan Solbrig, Giampietro Tecchiolli, Tilo Wettig, Gianpaolo Zanier

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Tags: Benchmarking, Computational Physics, Computer science, High Energy Physics - Lattice, Intel Xeon Phi

February 22, 2015 by hgpu

cuLGT: Lattice Gauge Fixing on GPUs

Hannes Vogt, Mario Schrock

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Tags: Computational Physics, CUDA, High Energy Physics - Lattice, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, Package, Physics, Tesla K20

December 12, 2014 by hgpu

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BLOCKBENCH: A Framework for Analyzing Private Blockchains

Blockchain Goes Green? Part II: Characterizing the Performance and Cost of Blockchains on the Cloud and at the Edge

hls4ml: Machine learning on FPGAs using HLS

Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml

AnySeq/GPU: A Novel Approach for Faster Sequence Alignment on GPUs

AnySeq/GPU: A Novel Approach for Faster Sequence Alignment on GPUs

GPJSON: GPU-based JSON data processing system accessible via all GraalVM languages

GPU-based JSON data processing using structural indexes

NEPTUNE: Network- and GPU-aware management of serverless functions at the edge

NEPTUNE: Network- and GPU-aware Management of Serverless Functions at the Edge

HeCBench: a collection of Heterogeneous Computing benchmarks written with CUDA, HIP, SYCL (DPC++), and OpenMP-4.5

Experience of Migrating a Parallel Graph Coloring Program from CUDA to SYCL

cuPSO: GPU Parallelization for Particle Swarm Optimization Algorithms

cuPSO: GPU Parallelization for Particle Swarm Optimization Algorithms

WARPSPEED: An analytic Data Volume and Performance Estimator for GPU Kernels

Analytical Performance Estimation during Code Generation on Modern GPUs

Celerity HLA: A high-level API on top of Celerity to support functional, C++20 range-adaptors-like patterns

The Celerity High-level API: C++20 for Accelerator Clusters

GPU-Sched

CASE: A Compiler-Assisted SchEduling Framework for Multi-GPU Systems

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