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Comparison of HPC Architectures for Computing All-Pairs Shortest Paths. Intel Xeon Phi KNL vs NVIDIA Pascal

Manuel Costanzo, Enzo Rucci, Ulises Costi, Franco Chichizola, Marcelo Naiouf

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Tags: Algorithms, All-Pairs Distance, Computer science, CUDA, HPC, Intel, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan X, Package

May 23, 2021 by hgpu

NPBench: A Benchmarking Suite for High-Performance NumPy

Alexandros Nikolaos Ziogas, Tal Ben-Nun, Timo Schneider, Torsten Hoefler

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Tags: Benchmarking, Computer science, CUDA, HPC, Linear Algebra, nVidia, Package, Performance, Python, Tesla V100

May 16, 2021 by hgpu

Performance Assessment of using OpenCL on FPGA Systems for ODE Solvers

Patrick Tobias Haft

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Tags: Code generation, Computational biology, Computer science, Differential equations, FPGA, nVidia, nVidia GeForce GTX 980 Ti, ODEs, OpenCL, Optimization, Ordinary differential equations, Tesla K20, Thesis

May 16, 2021 by hgpu

Winograd Algorithm for AdderNet

Wenshuo Li, Hanting Chen, Mingqiang Huang, Xinghao Chen, Chunjing Xu, Yunhe Wang

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Tags: Algorithms, CNN, Computer science, Deep learning, FPGA, Machine learning, Neural networks, Performance

May 16, 2021 by hgpu

Raster Time Series: Learning and Processing

Johannes Drönner

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Tags: AMD Radeon RX 580, ATI, Computer science, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, OpenCL, Sensing, Thesis, Visualization

May 16, 2021 by hgpu

PeriPy – A High Performance OpenCL Peridynamics Package

B. Boys, T. J. Dodwell, M. Hobbs, M. Girolami

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Tags: Benchmarking, Computer science, Heterogeneous systems, nVidia, nVidia GeForce RTX 2080 Ti, OpenCL, Package, Python

May 16, 2021 by hgpu

Performance Evaluation and Improvements of the PoCL Open-Source OpenCL Implementation on Intel CPUs

Tobias Baumann, Matthias Noack, Thomas Steinke

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Tags: Benchmarking, Computer science, LLVM, OpenCL, Package, Video

May 9, 2021 by hgpu

Sylkan: Towards a Vulkan Compute Target Platform for SYCL

Peter Thoman, Daniel Gogl, Thomas Fahringer

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Tags: Benchmarking, Computer science, Data parallelism, Heterogeneous systems, OpenCL, SYCL, Video, Vulkan

May 9, 2021 by hgpu

Irregularity Mitigation and Portability Abstractions for Accelerated Sparse Matrix Factorization

Daniel Thürck

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Tags: Algorithms, Computer science, Factorization, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan V, OpenCL, Sparse matrix, Thesis

May 9, 2021 by hgpu

Efficacy of Images Versus Data Buffers: Optimizing Interactive Applications Utilizing OpenCL for Scientific Visualization

Donald W. Johnson, T. J. Jankun-Kelly

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Tags: AMD Radeon HD 7950, ATI, Computer science, Interactive application, OpenCL, Visualization

May 9, 2021 by hgpu

DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learning

Sheldon Fung, Xuequan Lu, Chao Zhang, Chang-Tsun Li

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia GeForce RTX 2080 Ti, PyTorch

May 2, 2021 by hgpu

Enabling Energy-Efficient DNN Training on Hybrid GPU-FPGA Accelerators

Xin He, Jiawen Liu, Zhen Xie, Hao Chen, Guoyang Chen, Weifeng Zhang, Dong Li

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Tags: Computer science, Deep learning, Design space exploration, FPGA, Hybrid computing, nVidia, OpenCL, Tesla V100

May 2, 2021 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

Comparison of HPC Architectures for Computing All-Pairs Shortest Paths. Intel Xeon Phi KNL vs NVIDIA Pascal

NPBench: A Benchmarking Suite for High-Performance NumPy

Performance Assessment of using OpenCL on FPGA Systems for ODE Solvers

Winograd Algorithm for AdderNet

Raster Time Series: Learning and Processing

PeriPy – A High Performance OpenCL Peridynamics Package

Performance Evaluation and Improvements of the PoCL Open-Source OpenCL Implementation on Intel CPUs

Sylkan: Towards a Vulkan Compute Target Platform for SYCL

Irregularity Mitigation and Portability Abstractions for Accelerated Sparse Matrix Factorization

Efficacy of Images Versus Data Buffers: Optimizing Interactive Applications Utilizing OpenCL for Scientific Visualization

DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learning

Enabling Energy-Efficient DNN Training on Hybrid GPU-FPGA Accelerators

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)