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Understanding GPU Programming for Statistical Computation: Studies in Massively Parallel Massive Mixtures

Marc A. Suchard, Quanli Wang, Cliburn Chan, Jacob Frelinger, Andrew Cron, Mike West

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Tags: Bayesian, CUDA, Mathematics, nVidia, nVidia GeForce 9600 M GT, nVidia GeForce GTX 285, Package, Statistics, Tesla C1060

March 4, 2011 by hgpu

On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods

Anthony Lee, Christopher Yau, Michael B. Giles, Arnaud Doucet, Christopher C. Holmes

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Tags: CUDA, Mathematics, Monte Carlo simulation, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 280, Package, Statistics

November 8, 2010 by hgpu

Parallel hyperbolic PDE simulation on clusters: Cell versus GPU

Scott Rostrup, Hans De Sterck

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Tags: Cell processor, CUDA, Hyperbolic PDEs, Hyperbolic system, Mathematics, nVidia, Package, Tesla C2050, Tesla T10

November 7, 2010 by hgpu

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

chemtrain: Training Molecular Dynamics Potentials in JAX

chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations

microSYCL: SYCL micro-benchmarks repository

Exploring SYCL as a Portability Layer for High-Performance Computing on CPUs

XaaS containers

Acceleration as a Service (XaaS) Source Containers

SYCL Container

Exploring SYCL for batched kernels with memory allocations

CASS: Cuda-Amd aSSembly

CASS: Nvidia to AMD Transpilation with Data, Models, and Benchmark

Cluser of smartphones for edge computing application using TensorFlow

Low-cost edge computing using upcycled smartphones

CFAL-bench

Comparing Parallel Functional Array Languages: Programming and Performance

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

Can Large Language Models Predict Parallel Code Performance?

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