high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » paper

GPU-Accelerated Atari Emulation for Reinforcement Learning

Steven Dalton, Iuri Frosio, Michael Garland

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX Titan V, Package, Tesla V100

July 28, 2019 by hgpu

Benchmarking TPU, GPU, and CPU Platforms for Deep Learning

Yu (Emma)Wang, Gu-Yeon Wei, David Brooks

View

Download (PDF)

Tags: Benchmarking, Cloud, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, Performance, Tesla V100, TPU

July 28, 2019 by hgpu

MagmaDNN: Towards High-Performance Data Analytics and Machine Learning for Data-Driven Scientific Computing

Daniel Nichols, Nathalie-Sofia Tomov, Frank Betancourt, Stanimire Tomov, Kwai Wong, Jack Dongarra

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, HPC, Linear Algebra, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1050Ti, Package

July 26, 2019 by hgpu

Assessing the feasibility of OpenCL CPU implementations for agent-based simulations

Nuno Fachada, Agostinho C. Rosa

View

Download (PDF)

Tags: Agent-based modeling, AMD, cpu, Intel, OpenCL, simulation

July 24, 2019 by fakenmc

Sorting on FPGAs using Merge Trees

Nikola Samardzic

View

Download (PDF)

Tags: Algorithms, Computer science, FPGA, Sorting

July 21, 2019 by hgpu

A Versatile Software Systolic Execution Model for GPU Memory-Bound Kernels

Peng Chen, Mohamed Wahib, Shinichiro Takizawa, Ryousei Takano, Satoshi Matsuoka

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, nVidia, Package, Stencil computation, Tesla P100, Tesla V100

July 21, 2019 by hgpu

GRN: Gated Relation Network to Enhance Convolutional Neural Network for Named Entity Recognition

Hui Chen, Zijia Lin, Guiguang Ding, Jianguang Lou, Yusen Zhang, Borje Karlsson

View

Download (PDF)

Tags: Computer science, Neural networks, NLP, nVidia, Tesla P100

July 21, 2019 by hgpu

A Highly Efficient Distributed Deep Learning System For Automatic Speech Recognition

Wei Zhang, Xiaodong Cui, Ulrich Finkler, George Saon, Abdullah Kayi, Alper Buyuktosunoglu, Brian Kingsbury, David Kung, Michael Picheny

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Deep learning, Distributed computing, GPU cluster, nVidia, OpenMPI, Speech recognition, Tesla V100

July 21, 2019 by hgpu

Block based Singular Value Decomposition approach to matrix factorization for recommender systems

Prasad Bhavana, Vikas Kumar, Vineet Padmanabhan

View

Download (PDF)

Source codes

Tags: AI, Algorithms, Computer science, CUDA, Factorization, Machine learning, nVidia, Package, Tesla M40

July 21, 2019 by hgpu

Out-of-core singular value decomposition

Vadim Demchik, Miroslav Bačák, Stefan Bordag

View

Download (PDF)

Tags: BLAS, Computer science, Mathematical Software, Numerical Analysis, Out of core, Sparse matrix

July 16, 2019 by hgpu

On the Portability of CPU-Accelerated Applications via Automated Source-to-Source Translation

Paul Sathre, Mark Gardner, Wu-chun Feng

View

Download (PDF)

Source codes

Tags: AMD FirePro S9150, ATI, Compilers, Computer science, CUDA, FPGA, nVidia, OpenCL, Package, performance portability, Tesla K80

July 14, 2019 by hgpu

HashGraph – Scalable Hash Tables Using A Sparse Graph Data Structure

Oded Green

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Databases, Graph theory, nVidia, nVidia Quadro GV100

July 14, 2019 by hgpu

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

LLOR: Automatic Repair of OpenMP Programs

LLOR: Automated Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

Unified schemes for directive-based GPU offloading

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Applications

GPU-Accelerated Atari Emulation for Reinforcement Learning

MagmaDNN: Towards High-Performance Data Analytics and Machine Learning for Data-Driven Scientific Computing

Assessing the feasibility of OpenCL CPU implementations for agent-based simulations

Sorting on FPGAs using Merge Trees

A Versatile Software Systolic Execution Model for GPU Memory-Bound Kernels

GRN: Gated Relation Network to Enhance Convolutional Neural Network for Named Entity Recognition

A Highly Efficient Distributed Deep Learning System For Automatic Speech Recognition

Block based Singular Value Decomposition approach to matrix factorization for recommender systems

Out-of-core singular value decomposition

On the Portability of CPU-Accelerated Applications via Automated Source-to-Source Translation

HashGraph – Scalable Hash Tables Using A Sparse Graph Data Structure

Recent source codes

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

Most viewed papers (last 30 days)