high performance computing on graphics processing units: hgpu.org

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Automatic Tuning of Local Memory Use on GPGPUs

Tianyi David Han, Tarek S. Abdelrahman

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Tags: Benchmarking, Computer science, Machine learning, nVidia, OpenCL, Performance, Tesla M2090

December 26, 2014 by hgpu

Accelerating Correlation Power Analysis Using Graphics Processing Units

Hasindu Gamaarachchi, Roshan Ragel, Darshana Jayasinghe

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Tags: AES, Algorithms, Computer science, CUDA, nVidia, Performance, Security, Tesla C2075

December 26, 2014 by hgpu

Easy-to-Use On-the-Fly Binary Program Acceleration on Many-Cores

Marvin Damschen, Christian Plessl

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Source codes

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

December 15, 2014 by hgpu

Heuristics for Conversion Process of GPU’s Kernels for Multiples Kernels with Concurrent Optimization Divergence

Jose Ritomar Carneiro Torquato, Esteban Walter Gonzalez Clua

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Performance, Tesla K10, Tesla K20

December 14, 2014 by hgpu

Lattice QCD with Domain Decomposition on Intel Xeon Phi Co-Processors

Simon Heybrock, Balint Joo, Dhiraj D. Kalamkar, Mikhail Smelyanskiy, Karthikeyan Vaidyanathan, Tilo Wettig, Pradeep Dubey

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

December 9, 2014 by hgpu

Improving GPU Performance by Regrouping CPU-Memory Data

Deepthi Gummadi

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Tags: ARM, Computer science, CUDA, nVidia, Performance, Tesla C2075, Tesla K20, Thesis

November 25, 2014 by hgpu

A Self-Optimizing Framework for Developing Metrology Software on Massive Parallel Processor Architectures

T. Beier

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Tags: Algorithms, ATI, ATI Radeon HD 7750, Computer science, nVidia, nVidia GeForce GTX 480, OpenCL, Performance

November 25, 2014 by hgpu

Automatic Performance Tuning of Pipeline Patterns for Heterogeneous Parallel Architectures

E. Bajrovic, S. Benkner

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Tags: Computer science, Heterogeneous systems, nVidia, OpenCL, OpenCV, Performance, Tesla C2050, Tesla K20

November 20, 2014 by hgpu

The Implementation of a Real-Time Polyphase Filter

Karel Adamek, Jan Novotny, Wes Armour

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Tags: CUDA, Intel Xeon Phi, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 750 Ti, Performance, Signal processing, Tesla K40

November 16, 2014 by hgpu

Locality-Aware Mapping of Nested Parallel Patterns on GPUs

HyoukJoong Lee, Kevin J. Brown, Arvind K. Sujeeth, Tiark Rompf, Kunle Olukotun

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Tags: Code generation, Computer science, CUDA, nVidia, Performance, Tesla K20

November 12, 2014 by hgpu

Code Optimization on Kepler GPUs and Xeon Phi

Yong-Chull Jang, Hwancheol Jeong, Jangho Kim, Weonjong Lee, Jeonghwan Pak, Yuree Chung (SWME Collaboration)

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Tags: CUDA, High Energy Physics - Lattice, Intel Xeon Phi, Maxwell's equations, MPI, nVidia, nVidia GeForce GTX 980, nVidia GeForce GTX Titan, OpenMP, Performance, Physics, QCD, Tesla K40

November 12, 2014 by hgpu

Profiling of Data-Parallel Processors

Daniel Kruck, Holger Froening

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Tags: Computer science, CUDA, nVidia, Performance, Tesla K20

November 3, 2014 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Automatic Tuning of Local Memory Use on GPGPUs

Accelerating Correlation Power Analysis Using Graphics Processing Units

Easy-to-Use On-the-Fly Binary Program Acceleration on Many-Cores

Heuristics for Conversion Process of GPU’s Kernels for Multiples Kernels with Concurrent Optimization Divergence

Lattice QCD with Domain Decomposition on Intel Xeon Phi Co-Processors

Improving GPU Performance by Regrouping CPU-Memory Data

A Self-Optimizing Framework for Developing Metrology Software on Massive Parallel Processor Architectures

Automatic Performance Tuning of Pipeline Patterns for Heterogeneous Parallel Architectures

The Implementation of a Real-Time Polyphase Filter

Locality-Aware Mapping of Nested Parallel Patterns on GPUs

Code Optimization on Kepler GPUs and Xeon Phi

Profiling of Data-Parallel Processors

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

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

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

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

EnergyUCB-Bandit

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