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Benchmarking optimization algorithms for auto-tuning GPU kernels

Richard Schoonhoven, Ben van Werkhoven, Kees Joost Batenburg

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Tags: AMD Radeon Instinct Mi50, ATI, Auto-Tuning, Benchmarking, Computer science, CUDA, nVidia, nVidia A100, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX Titan X, nVidia Titan RTX, OpenCL, Performance, pyCUDA, PyOpenCL, Tesla K20, Tesla P100, Tesla V100

October 9, 2022 by hgpu

Designing a high-performance boundary element library with OpenCL and Numba

T. Betcke, M. W. Scroggs

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Tags: Computer science, HPC, nVidia, nVidia Quadro RTX 3000, OpenCL, Package, PyOpenCL, Python

July 18, 2021 by hgpu

linus: Conveniently explore, share, and present large-scale biological trajectory data from a web browser

Johannes Waschke, Mario Hlawitschka, Kerim Anlas, Vikas Trivedi, Ingo Roeder, Jan Huisken, Nico Scherf

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Tags: Biology, OpenCL, Package, PyOpenCL, Python

January 10, 2021 by hgpu

PyMatting: A Python Library for Alpha Matting

Thomas Germer, Tobias Uelwer, Stefan Conrad, Stefan Harmeling

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Tags: Computer vision, CUDA, Image processing, nVidia, OpenCL, Package, PyOpenCL, Python

April 5, 2020 by hgpu

APL on GPUs: A TAIL from the Past, Scribbled in Futhark

Troels Henriksen, Martin Dybdal, Henrik Urms, Anna Sofie Kiehn, Daniel Gavin, Hjalte Abelskov, Martin Elsman, Cosmin Oancea

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Tags: Compilers, Computer science, nVidia, nVidia GeForce GTX 780 Ti, OpenCL, Package, PyOpenCL, Python, Visualization

October 4, 2016 by hgpu

OpenCL-accelerated object classification in video streams using Spatial Pooler of Hierarchical Temporal Memory

Maciej Wielgosz, Marcin Pietron

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Tags: Algorithms, AMD Radeon R9 390, ATI, Computer science, Computer vision, Machine learning, OpenCL, Package, PyOpenCL, Python

August 8, 2016 by hgpu

GPU computing with OpenCL to model 2D elastic wave propagation: exploring memory usage

Ursula Iturraran-Viveros, Miguel Molero-Armenta

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Tags: Condensed matter, Instrumentation and measurement, nVidia, OpenCL, Package, Physics, PyOpenCL, Python

August 21, 2015 by hgpu

A Parallel Implementation of the Galerkin Method for Solving Partial Differential Equations on a Triangular Mesh

Rachel N. Hess

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Tags: Differential equations, FEM, Finite element method, Mathematics, OpenCL, Partial differential equations, PDEs, PyOpenCL, Thesis, Triangular meshes

June 7, 2015 by hgpu

PyFAI: a Python library for high performance azimuthal integration on GPU

Jerome Kieffer, Giannis Ashiotis

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Tags: Astrophysics, ATI, ATI FirePro V7800, Instrumentation and Methods for Astrophysics, Intel Xeon Phi, nVidia, nVidia GeForce GTX 750 Ti, OpenCL, Package, PyOpenCL, Python, Tesla K20

December 22, 2014 by hgpu

Loo.py: transformation-based code generation for GPUs and CPUs

Andreas Klockner

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Tags: ATI, ATI Radeon HD 7990, Code generation, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, OpenCL, Package, Programming Languages, PyOpenCL, Python

June 2, 2014 by hgpu

Nengo: a Python tool for building large-scale functional brain models

Trevor Bekolay, James Bergstra, Eric Hunsberger, Travis DeWolf, Terrence C. Stewart, Daniel Rasmussen, Xuan Choo, Aaron Russell Voelker, Chris Eliasmith

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Tags: ATI, ATI Radeon HD 7970, Biology, Neuroscience, nVidia, nVidia GeForce GTX 280, OpenCL, Package, PyOpenCL, Python

January 9, 2014 by hgpu

Computing finite models using free Boolean generators

Zarko Mijajlovic, Aleksandar Pejovic

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Tags: Computer science, Logic in Computer Science, OpenCL, Package, PyOpenCL

October 29, 2013 by hgpu

Genomics-GPU: A Benchmark Suite for GPU-accelerated Genome Analysis

Genomics-GPU: A Benchmark Suite for GPU-accelerated Genome Analysis

AutoDock for GPUs and other accelerators

Experiences Migrating CUDA to SYCL: A Molecular Docking Case Study

spotPython: Sequential Parameter Optimization in Python

PyTorch Hyperparameter Tuning – A Tutorial for spotPython

Test benchmarks for CELERITY

An Asynchronous Dataflow-Driven Execution Model For Distributed Accelerator Computing

Dragon-Alpha&cu32: A Java-based Tensor Computing Framework With its High-Performance CUDA Library

Dragon-Alpha&cu32: A Java-based Tensor Computing Framework With its High-Performance CUDA Library

Beehive SPIR-V Toolkit

Experiences in Building a Composable and Functional API for Runtime SPIR-V Code Generation

TorchBench: a collection of open source benchmarks used to evaluate PyTorch performance

TorchBench: Benchmarking PyTorch with High API Surface Coverage

Prediction of Performance and Power Consumption of GPGPU Applications

Prediction of Performance and Power Consumption of GPGPU Applications

Descend: an attempt at safe imperative GPU programming

Descend: A Safe GPU Systems Programming Language

Redwood heterogeneous framework

Redwood: Flexible and Portable Heterogeneous Tree Traversal Workloads

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