high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

Automatic Optimization of OpenCL-Based Stencil Codes for FPGAs and Its Evaluation

Tsukasa Endo, Hasitha Muthumala Waidyasooriya, Masanori Hariyama

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Tags: Computer science, FPGA, OpenCL, Performance, Stencil computation

April 15, 2018 by hgpu

Implementing Push-Pull Efficiently in GraphBLAS

Carl Yang, Aydin Buluc, John D. Owens

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Tags: Algorithm optimization, Algorithms, BLAS, Computer science, CUDA, Graph theory, Linear Algebra, nVidia, Sparse matrix, Tesla K40

April 15, 2018 by hgpu

G-NET: Effective GPU Sharing in NFV Systems

Kai Zhang, Bingsheng He, Jiayu Hu, Zeke Wang, Bei Hua, Jiayi Meng, Lishan Yang

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan X, Virtualization

April 15, 2018 by hgpu

Towards a Unified CPU-GPU code hybridization: A GPU Based Optimization Strategy Efficient on Other Modern Architectures

Ludomir Oteski, Guillaume De Verdiere, Sylvain Contassot-Vivier, Stephane Vialle, Juliet Ryan

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Tags: Computer science, CUDA, Fluid dynamics, Intel Xeon Phi, nVidia, Tesla K20, Tesla P100

April 15, 2018 by hgpu

Evaluating Performance Tradeoffs on the Radeon Open Compute Platform

Yifan Sun, Saoni Mukherjee, Trinayan Baruah, Shi Dong, Julian Gutierrez, Prannoy Mohan, David Kaeli

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Source codes

Tags: AMD R9 Nano, ATI, Computer science, Heterogeneous systems, HSA, nVidia, nVidia GeForce GTX 1080, OpenCL, Package

April 7, 2018 by hgpu

A Survey of Techniques for Improving Security of GPUs

Sparsh Mittal, S.B. Abhinaya, Manish Reddy, Irfan Ali

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Tags: Computer science, Security, survey

April 7, 2018 by hgpu

High-performance sparse matrix-matrix products on Intel KNL and multicore architectures

Yusuke Nagasaka, Satoshi Matsuoka, Ariful Azad, Aydin Buluc

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Tags: Algorithms, Computer science, Intel Xeon Phi, Matrix multiplication, Sparse matrix

April 7, 2018 by hgpu

Verification of Program Parallelization

Saeed Darabi

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Tags: Computer science, OpenCL, OpenMP, Parallel programming, Thesis

April 7, 2018 by hgpu

Sparse Matrix-Matrix Multiplication on Multilevel Memory Architectures : Algorithms and Experiments

Mehmet Deveci, Simon D. Hammond, Michael M. Wolf, Sivasankaran Rajamanickam

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, Sparse matrix, Tesla P100

April 7, 2018 by hgpu

HDArray: Parallel Array Interface for Distributed Heterogeneous Devices

Hyun Dok Cho, Okwan Kwon, Samuel P. Midkiff

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Tags: Computer science, Distributed computing, Heterogeneous systems, MPI, nVidia, OpenCL, Tesla K80, Tesla P100

March 31, 2018 by hgpu

A Comparison between GPU-based Volume Ray Casting Implementations: Fragment Shader, Compute Shader, OpenCL, and CUDA

Francisco Sans, Rhadames Carmona

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 660, OpenCL, OpenGL, Performance, Rendering

March 31, 2018 by hgpu

Face Recognition with Hybrid Efficient Convolution Algorithms on FPGAs

Chuanhao Zhuge, Xinheng Liu, Xiaofan Zhang, Sudeep Gummadi, Jinjun Xiong, Deming Chen

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Tags: CNN, Computer science, Computer vision, FFT, FPGA, HLS

March 31, 2018 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

Automatic Optimization of OpenCL-Based Stencil Codes for FPGAs and Its Evaluation

Implementing Push-Pull Efficiently in GraphBLAS

G-NET: Effective GPU Sharing in NFV Systems

Towards a Unified CPU-GPU code hybridization: A GPU Based Optimization Strategy Efficient on Other Modern Architectures

Evaluating Performance Tradeoffs on the Radeon Open Compute Platform

A Survey of Techniques for Improving Security of GPUs

High-performance sparse matrix-matrix products on Intel KNL and multicore architectures

Verification of Program Parallelization

Sparse Matrix-Matrix Multiplication on Multilevel Memory Architectures : Algorithms and Experiments

HDArray: Parallel Array Interface for Distributed Heterogeneous Devices

A Comparison between GPU-based Volume Ray Casting Implementations: Fragment Shader, Compute Shader, OpenCL, and CUDA

Face Recognition with Hybrid Efficient Convolution Algorithms on FPGAs

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)