high performance computing on graphics processing units: hgpu.org

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Evaluating the Efficiency of CPUs, GPUs and FPGAs on a Near-Duplicate Document Detection Via OpenCL

Ercan Canhasi

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Tags: Computer science, FPGA, Machine learning, NLP, OpenCL

July 5, 2018 by hgpu

A Survey on Agent-based Simulation using Hardware Accelerators

Jiajian Xiao, Philipp Andelfinger, David Eckhoff, Wentong Cai, Alois Knoll

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, OpenCL, Overview

July 5, 2018 by hgpu

XGBoost: Scalable GPU Accelerated Learning

Rory Mitchell, Andrey Adinets, Thejaswi Rao, Eibe Frank

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Tags: Computer science, CUDA, Java, Machine learning, nVidia, Package, Python, R, Scala, Tesla V100

July 5, 2018 by hgpu

Directive-Based, High-Level Programming and Optimizations for High-Performance Computing with FPGAs

Jacob Lambert, Seyong Lee, Jungwon Kim, Jeffrey S. Vetter, Allen D. Malony

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Tags: Computer science, FPGA, nVidia, OpenACC, OpenCL, Tesla K40

July 1, 2018 by hgpu

Analysis-driven Engineering of Comparison-based Sorting Algorithms on GPUs

Ben Karsin, Volker Weichert, Henri Casanova, John Iacono, Nodari Sitchinava

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 770, nVidia Quadro M 4000, Performance, Sorting, Tesla K40

July 1, 2018 by hgpu

Reducing the Cost of Heuristic Generation with Machine Learning

William F. Ogilvie

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Tags: Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX Titan, OpenCL, Thesis

July 1, 2018 by hgpu

Compiler Fuzzing through Deep Learning

Chris Cummins, Pavlos Petoumenos, Hugh Leather, Alastair Murray

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Tags: Compilers, Computer science, Deep learning, Intel Xeon Phi, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 780, OpenCL, Package

July 1, 2018 by hgpu

Introducing Parallelism to the Ranges TS

Gordon Brown, Christopher Di Bella, Michael Haidl, Toomas Remmelg, Ruyman Reyes, Michel Steuwer

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Tags: Computer science, Heterogeneous systems, OpenCL, Package, SYCL

June 28, 2018 by hgpu

Analyzing Memory Accesses for Performance and Correctness of Parallel Programs

Tim Cramer

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Tags: Computer science, Heterogeneous systems, HPC, Intel Xeon Phi, Memory model, OpenMP, Parallel programming, Thesis

June 28, 2018 by hgpu

Improving tasks throughput on accelerators using OpenCL command concurrency

A.J. Lazaro-Munoz, J.M. Gonzalez-Linares, J. Gomez-Luna, N. Guil

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Tags: AMD Radeon R9, ATI, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Performance, Task scheduling, Tesla K20

June 28, 2018 by hgpu

Migrating from OpenGL ES to Vulkan

Imagination Technologies Limited

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Tags: 3D Graphics and Realism, OpenGL, Rendering, Vulkan

June 28, 2018 by hgpu

Go game move prediction using convolutional neural network

Marek Korenciak

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Tags: Caffe, CNN, Computer science, CUDA, Deep learning, Games, nVidia, nVidia GeForce GTX 1080 Ti, Package, Thesis

June 24, 2018 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

Applications

Evaluating the Efficiency of CPUs, GPUs and FPGAs on a Near-Duplicate Document Detection Via OpenCL

A Survey on Agent-based Simulation using Hardware Accelerators

XGBoost: Scalable GPU Accelerated Learning

Directive-Based, High-Level Programming and Optimizations for High-Performance Computing with FPGAs

Analysis-driven Engineering of Comparison-based Sorting Algorithms on GPUs

Reducing the Cost of Heuristic Generation with Machine Learning

Compiler Fuzzing through Deep Learning

Introducing Parallelism to the Ranges TS

Analyzing Memory Accesses for Performance and Correctness of Parallel Programs

Improving tasks throughput on accelerators using OpenCL command concurrency

Migrating from OpenGL ES to Vulkan

Go game move prediction using convolutional neural network

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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