high performance computing on graphics processing units: hgpu.org

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Transparent Acceleration for Heterogeneous Platforms With Compilation to OpenCL

Heinrich Riebler, Gavin Vaz, Tobias Kenter, Christian Plessl

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Tags: Compilers, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Tesla K20

May 1, 2019 by hgpu

The Risks of WebGL: Analysis, Evaluation and Detection

Alex Belkin, Nethanel Gelernter, Israel Cidon

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Tags: Computer science, nVidia, nVidia GeForce GTX 1080, Security, WebGL

May 1, 2019 by hgpu

A mechanism for balancing accuracy and scope in cross-machine black-box GPU performance modeling

James D. Stevens

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Tags: AMD Radeon R9 Fury, ATI, Code generation, Computer science, Finite difference, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX Titan X, OpenCL, Performance, Tesla C2070, Tesla K40

April 28, 2019 by hgpu

Chunkflow: Distributed Hybrid Cloud Processing of Large 3D Images by Convolutional Nets

Jingpeng Wu, William M. Silversmith, H. Sebastian Seung

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Tags: Cloud, CNN, Computer science, CUDA, Deep learning, Electron microscopy, Image processing, Microscopy, nVidia, nVidia GeForce GTX 970, Package, Tesla K80

April 28, 2019 by hgpu

Wasserstein-Fisher-Rao Document Distance

Zihao Wang, Datong Zhou, Yong Zhang, Hao Wu, Chenglong Bao

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Tags: Computer science, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX 1080 Ti

April 28, 2019 by hgpu

GPU-based Efficient Join Algorithms on Hadoop

Hongzhi Wang, Ning Li, Zheng Wang, Jianing Li

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Tags: Algorithms, Computer science, CUDA, Databases, Hadoop, nVidia

April 28, 2019 by hgpu

Loop Perforation in OpenACC

Ahmad Lashgar, Ehsan Atoofian, Amirali Baniasadi

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Tags: Computer science, CUDA, OpenACC, OpenCL, Package, Performance

April 20, 2019 by hgpu

On Optimizing Complex Stencils on GPUs

Prashant Singh Rawat, Miheer Vaidya, Aravind Sukumaran-Rajam, Atanas Rountev, Louis-Noël Pouchet, P. Sadayappan

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Tags: Code generation, Computer science, CUDA, nVidia, Stencil computation, Tesla P100

April 20, 2019 by hgpu

A Comparative Study of Asynchronous Many-Tasking Runtimes: Cilk, Charm++, ParalleX and AM++

Abhishek Kulkarni, Andrew Lumsdaine

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Tags: Computer science, HPC, MPI

April 20, 2019 by hgpu

Real world applications of Artificial Intelligence on constrained hardware

Wiebe Van Ranst

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Tags: Artificial intelligence, Computer science, Computer vision, Image processing, nVidia, nVidia Jetson TX2, OpenCL, Thesis

April 20, 2019 by hgpu

Concurrent query processing in a GPU-based database system

Hao Li, Yi-Cheng Tu, Bo Zeng

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX Titan X, Package

April 20, 2019 by hgpu

Accelerated Neural Networks on OpenCL Devices Using SYCL-DNN

Rod Burns, John Lawson, Duncan McBain, Daniel Soutar

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Tags: Computer science, Computer vision, Deep learning, Machine learning, Neural networks, nVidia, OpenCL, Package, SYCL

April 14, 2019 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Transparent Acceleration for Heterogeneous Platforms With Compilation to OpenCL

The Risks of WebGL: Analysis, Evaluation and Detection

A mechanism for balancing accuracy and scope in cross-machine black-box GPU performance modeling

Wasserstein-Fisher-Rao Document Distance

GPU-based Efficient Join Algorithms on Hadoop

Loop Perforation in OpenACC

On Optimizing Complex Stencils on GPUs

A Comparative Study of Asynchronous Many-Tasking Runtimes: Cilk, Charm++, ParalleX and AM++

Real world applications of Artificial Intelligence on constrained hardware

Concurrent query processing in a GPU-based database system

Accelerated Neural Networks on OpenCL Devices Using SYCL-DNN

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

Most viewed papers (last 30 days)