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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

Easy and Efficient Transformer: Scalable Inference Solution For large NLP mode

Gongzheng li, Yadong Xi, Jingzhen Ding, Duan Wang, Bai Liu, Changjie Fan, Xiaoxi Mao, Zeng Zhao

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Tags: Computer science, CUDA, NLP, nVidia, nVidia GeForce RTX 2080 Ti, Package, Tesla A100

May 2, 2021 by hgpu

tcFFT: Accelerating Half-Precision FFT through Tensor Cores

Binrui Li, Shenggan Cheng, James Lin

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Tags: Computer science, FFT, Mixed precision, nVidia, nVidia DGX-2, nVidia DGX-A100, Tesla V100

May 2, 2021 by hgpu

How to Train BERT with an Academic Budget

Peter Izsak, Moshe Berchansky, Omer Levy

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Tags: Artificial intelligence, Computer science, Deep learning, Machine learning, NLP, nVidia, nVidia GeForce GTX Titan V, Tesla V100

April 25, 2021 by hgpu

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Evaluation of Rust for GPGPU high performance computing

Evaluation of Rust for GPGPU high-performance computing

SCAMP: CPU/GPU Implementation of the SCAMP algorithm for computing the matrix profile

Optimization of massive data applications on heterogeneous architectures

A Symbolic Emulator for Shuffle Synthesis on the NVIDIA PTX Code

FDAS: Fourier Domain Acceleration Search, FPGA-accelerated with OpenCL

Pulsar search acceleration using FPGAs and OpenCL templates

Implementation of a motion estimation algorithm for Intel FPGAs using OpenCL

Reeber: a library for shared- and distributed-memory parallel computation of merge trees

Fast Merge Tree Computation via SYCL

pocl: Portable Computing Language

Efficient OpenCL system integration of non-blocking FPGA accelerators

OneFlow: a deep learning framework designed to be user-friendly, scalable and efficient

AutoDDL: Automatic Distributed Deep Learning with Asymptotically Optimal Communication

Python Suite for Advanced General Ensemble Simulations

PySAGES: flexible, advanced sampling methods accelerated with GPUs

GPU load-balancing library for regular and irregular computations

A Programming Model for GPU Load Balancing

See all packages

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high performance computing on graphics processing units: hgpu.org

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

Easy and Efficient Transformer: Scalable Inference Solution For large NLP mode

tcFFT: Accelerating Half-Precision FFT through Tensor Cores

How to Train BERT with an Academic Budget

Recent source codes

Evaluation of Rust for GPGPU high performance computing

SCAMP: CPU/GPU Implementation of the SCAMP algorithm for computing the matrix profile

A Symbolic Emulator for Shuffle Synthesis on the NVIDIA PTX Code

FDAS: Fourier Domain Acceleration Search, FPGA-accelerated with OpenCL

Implementation of a motion estimation algorithm for Intel FPGAs using OpenCL

Reeber: a library for shared- and distributed-memory parallel computation of merge trees

pocl: Portable Computing Language

OneFlow: a deep learning framework designed to be user-friendly, scalable and efficient

Python Suite for Advanced General Ensemble Simulations

GPU load-balancing library for regular and irregular computations

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