high performance computing on graphics processing units: hgpu.org

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Advanced Joins on GPUs

Christos Bellas

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX Titan XP, Package, Thesis

March 27, 2022 by hgpu

Building a Performance Model for Deep Learning Recommendation Model Training on GPUs

Zhongyi Lin, Louis Feng, Ehsan K. Ardestani, Jaewon Lee, John Lundell, Changkyu Kim, Arun Kejariwal, John D. Owens

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Tags: Algorithms, Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX Titan XP, Package, Performance, Tesla P100, Tesla V100

January 23, 2022 by hgpu

GCN Inference Acceleration using High-Level Synthesis

Yi Chien Lin, Bingyi Zhang, Viktor Prasanna

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Tags: Computer science, Data parallelism, Design space exploration, FPGA, nVidia, nVidia GeForce GTX Titan XP, OpenCL, Package

October 10, 2021 by hgpu

Data-Oriented Language Implementation of Lattice-Boltzmann Method for Dense and Sparse Geometries

Tadeusz Tomczak

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Tags: cfd, CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia GeForce GTX Titan XP, Package

September 5, 2021 by hgpu

Easy and Efficient Agent-based Simulations with the OpenABL Language and Compiler

Biagio Cosenza, Nikita Popov, Ben Juurlink, Paul Richmond, Mozhgan Kabiri Chimeh, Carmine Spagnuolo, Gennaro Cordasco, Vittorio Scarano

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Tags: Compilers, Computer science, CUDA, DSL, nVidia, nVidia GeForce GTX Titan XP, Package

January 24, 2021 by hgpu

Montage: A Neural Network Language Model-Guided JavaScript Engine Fuzzer

Suyoung Lee, HyungSeok Han, Sang Kil Cha, Sooel Son

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Tags: Computer science, Java, Neural networks, nVidia, nVidia GeForce GTX Titan XP, Package, Python, PyTorch, Security

August 30, 2020 by hgpu

Accelerating Deep Learning Inference with Cross-Layer Data Reuse on GPUs

Xueying Wang, Guangli Li, Xiao Dong, Jiansong Li, Lei Liu, Xiaobing Feng

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Tags: Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan XP, Tesla P4

July 19, 2020 by hgpu

Fast Gunrock Subgraph Matching (GSM) on GPUs

Leyuan Wang, John D. Owens

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Tags: Computer science, Graph theory, nVidia, nVidia GeForce GTX Titan V, nVidia GeForce GTX Titan XP, Package

March 8, 2020 by hgpu

Porting tree-based hash table compression to GPGPU model checking

Danny Bergsma

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Tags: Algorithms, Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTX Titan XP, Package, Thesis

December 29, 2019 by hgpu

Performance Impact of Memory Channels on Sparse and Irregular Algorithms

Oded Green, James Fox, Jeffrey Young, Jun Shirako, David Bader

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan X, nVidia GeForce GTX Titan XP, Performance, Sparse, Tesla P100, Tesla V100

October 13, 2019 by hgpu

Memory-Efficient Object-Oriented Programming on GPUs

Matthias Springer

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 940 M, nVidia GeForce GTX 980, nVidia GeForce GTX Titan XP, Package, Programming Languages, Thesis

August 25, 2019 by hgpu

GPU-based Parallel Computation Support for Stan

Rok Cesnovar, Steve Bronder, Davor Sluga, Jure Demsar, Tadej Ciglaric, Sean Talts, Erik Strumbelj

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Tags: AMD Radeon R9 Fury, ATI, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan XP, OpenCL, Package, Tesla V100

July 10, 2019 by hgpu

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Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark

MapReduce for Counting Word Frequencies with MPI and GPUs

CoDL: Efficient CPU-GPU Co-execution for Deep Learning Inference on Mobile Devices

SYCLCOMP Utilities

On the Compilation Performance of Current SYCL Implementations

M1 GPUs for (scientific) computations in C++

Seamless GPU acceleration for C++ based physics with the Metal Shading Language on Apple’s M series unified chips

CUB: Cooperative primitives for CUDA C++

Onesweep: A Faster Least Significant Digit Radix Sort for GPUs

Simulator and workload generator for Edge-to-Cloud environments

FELARE: Fair Scheduling of Machine Learning Applications on Heterogeneous Edge Systems

See all packages

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high performance computing on graphics processing units: hgpu.org

Advanced Joins on GPUs

Building a Performance Model for Deep Learning Recommendation Model Training on GPUs

GCN Inference Acceleration using High-Level Synthesis

Data-Oriented Language Implementation of Lattice-Boltzmann Method for Dense and Sparse Geometries

Easy and Efficient Agent-based Simulations with the OpenABL Language and Compiler

Montage: A Neural Network Language Model-Guided JavaScript Engine Fuzzer

Accelerating Deep Learning Inference with Cross-Layer Data Reuse on GPUs

Fast Gunrock Subgraph Matching (GSM) on GPUs

Porting tree-based hash table compression to GPGPU model checking

Performance Impact of Memory Channels on Sparse and Irregular Algorithms

Memory-Efficient Object-Oriented Programming on GPUs

GPU-based Parallel Computation Support for Stan

Recent source codes

Rodinia Benchmarks for DPC++

DCA++: a state of the art implementation of the dynamical cluster approximation

tntorch - Tensor Network Learning with PyTorch

Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark

MapReduce for Counting Word Frequencies with MPI and GPUs

CoDL: Efficient CPU-GPU Co-execution for Deep Learning Inference on Mobile Devices

SYCLCOMP Utilities

M1 GPUs for (scientific) computations in C++

CUB: Cooperative primitives for CUDA C++

Simulator and workload generator for Edge-to-Cloud environments

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