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An asymmetric distributed shared memory model for heterogeneous parallel systems

Isaac Gelado, John E. Stone, Javier Cabezas, Sanjay Patel, Nacho Navarro, Wen-mei W. Hwu

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Tags: Computer science, CUDA, Memory, Memory model, nVidia, nVidia GeForce GTX 280

January 6, 2011 by hgpu

Shader-based tessellation to save memory bandwidth in a mobile multimedia processor

Kyusik Chung, Chang-Hyo Yu, Donghyun Kim, Lee-Sup Kim

Tags: Architecture, Computer science, Hardware, Memory, Tessellation

November 28, 2010 by hgpu

Complexity effective memory access scheduling for many-core accelerator architectures

George L. Yuan, Ali Bakhoda, Tor M. Aamodt

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Tags: Architecture, Computer science, CUDA, Hardware, Memory, nVidia

November 28, 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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