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Working With Incremental Spatial Data During Parallel (GPU) Computation

Robert Chisholm

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Tags: Agent-based modeling, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan V, Package, Thesis

February 9, 2020 by hgpu

Assessing the feasibility of OpenCL CPU implementations for agent-based simulations

Nuno Fachada, Agostinho C. Rosa

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Tags: Agent-based modeling, AMD, cpu, Intel, OpenCL, simulation

July 24, 2019 by fakenmc

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

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

Concurrent Scheduling of High-Level Parallel Programs on Multi-GPU Systems

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

WgPy: GPU-accelerated NumPy-like array library for web browsers

Microbenchmarking OpenMP target offload with Catch2

A Microbenchmark Framework for Performance Evaluation of OpenMP Target Offloading

SUperman: Highly Efficient Permanent Computation Library

SUperman: Efficient Permanent Computation on GPUs

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

pyATF: The Auto-Tuning Framework (ATF) in Python

pyATF: Constraint-Based Auto-Tuning in Python

TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators

TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators

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