high performance computing on graphics processing units: hgpu.org

hgpu.org » Signal processing

GRAFX: An Open-Source Library for Audio Processing Graphs in PyTorch

Sungho Lee, Marco Martínez-Ramírez, Wei-Hsiang Liao, Stefan Uhlich, Giorgio Fabbro, Kyogu Lee, Yuki Mitsufuji

View

Download (PDF)

Source codes

Tags: nVidia, nVidia GeForce RTX 3090, Package, PyTorch, Signal processing

August 18, 2024 by hgpu

FZ-GPU: A Fast and High-Ratio Lossy Compressor for Scientific Computing Applications on GPUs

Boyuan Zhang, Jiannan Tian, Sheng Di, Xiaodong Yu, Yunhe Feng, Xin Liang, Dingwen Tao, Franck Cappello

View

Download (PDF)

Source codes

Tags: Algorithms, Compression, Computer science, CUDA, nVidia, nVidia A100, nVidia RTX A4000, Package, Signal processing

May 7, 2023 by hgpu

Pulsar search acceleration using FPGAs and OpenCL templates

Julian Oppermann, Mitchell B. Mickaliger, Oliver Sinnen

View

Download (PDF)

Source codes

Tags: Astrophysics, Design space exploration, FPGA, OpenCL, Package, Physics, Signal processing

January 29, 2023 by hgpu

pyGSL: A Graph Structure Learning Toolkit

Max Wasserman, Gonzalo Mateos

View

Download (PDF)

Source codes

Tags: Computer science, Machine learning, Package, PyTorch, Signal processing

November 13, 2022 by hgpu

FPGA Implementation of Bluetooth Low Energy Physical Layer with OpenCL

Ganyong Mo

View

Download (PDF)

Tags: DSP, FPGA, OpenCL, Signal processing, Thesis

July 10, 2022 by hgpu

cuFINUFFT: a load-balanced GPU library for general-purpose nonuniform FFTs

Yu-hsuan Shih, Garrett Wright, Joakim Andén, Johannes Blaschke, Alex H. Barnett

View

Download (PDF)

Source codes

Tags: CUDA, FFT, Image reconstruction, Mathematical Software, Numerical Analysis, nVidia, Package, Signal processing, Tesla V100

February 21, 2021 by hgpu

High-Throughput Parallel Viterbi Decoder on GPU Tensor Cores

Alireza Mohammadidoost, Matin Hashemi

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, Signal processing, Tesla V100

December 6, 2020 by hgpu

Noise Removal from Remote Sensed Images by NonLocal Means with OpenCL Algorithm

Donatella Granata, Angelo Palombo, Federico Santini, Umberto Amato

View

Download (PDF)

Tags: Algorithms, Heterogeneous systems, nVidia, nVidia GeForce GTX 1650, OpenCL, Sensing, Signal processing

February 2, 2020 by hgpu

DBCSR: A Library for Dense Matrix Multiplications on Distributed GPU-Accelerated Systems

Ilia Sivkov, Alfio Lazzaro, Jurg Hutter

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Data mining, Linear Algebra, Machine learning, Matrix multiplication, nVidia, Package, Signal processing, Sparse matrix, Tesla P100

October 20, 2019 by hgpu

High Performance Computing via High Level Synthesis

Mehdi Roozmeh

View

Download (PDF)

Source codes

Tags: Computer science, Design space exploration, FPGA, Heterogeneous systems, HLS, Nearest neighbour, nVidia, OpenCL, Package, Signal processing, Thesis

August 18, 2019 by hgpu

Combining Multiple Optimised FPGA-based Pulsar Search Modules Using OpenCL

Haomiao Wang, Prabu Thiagaraj, Oliver Sinnen

View

Download (PDF)

Tags: Astrophysics, FPGA, OpenCL, Signal processing

June 17, 2018 by hgpu

Using reconfigurable computing technology to accelerate matrix decomposition and applications

Xinying Wang

View

Download (PDF)

Tags: Computer science, Data mining, Factorization, FPGA, Intel Xeon Phi, Matrix decomposition, Semantic indexing, Signal processing, Text mining, Thesis

December 28, 2017 by hgpu

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

* * *

high performance computing on graphics processing units: hgpu.org

GRAFX: An Open-Source Library for Audio Processing Graphs in PyTorch

FZ-GPU: A Fast and High-Ratio Lossy Compressor for Scientific Computing Applications on GPUs

Pulsar search acceleration using FPGAs and OpenCL templates

pyGSL: A Graph Structure Learning Toolkit

FPGA Implementation of Bluetooth Low Energy Physical Layer with OpenCL

cuFINUFFT: a load-balanced GPU library for general-purpose nonuniform FFTs

High-Throughput Parallel Viterbi Decoder on GPU Tensor Cores

Noise Removal from Remote Sensed Images by NonLocal Means with OpenCL Algorithm

DBCSR: A Library for Dense Matrix Multiplications on Distributed GPU-Accelerated Systems

High Performance Computing via High Level Synthesis

Combining Multiple Optimised FPGA-based Pulsar Search Modules Using OpenCL

Using reconfigurable computing technology to accelerate matrix decomposition and applications

Recent source codes

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Celerity Runtime: High-level C++ for Accelerator Clusters

wgpy: WebGL accelerated numpy-compatible array library for web browser

Microbenchmarking OpenMP target offload with Catch2

Most viewed papers (last 30 days)