high performance computing on graphics processing units: hgpu.org

Ilya Lashuk, Aparna Chandramowlishwaran, Harper Langston, Tuan A. Nguyen, Rahul Sampath, Aashay Shringarpure, Richard Vuduc, Lexing Ying, Denis Zorin, George Biros

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Tags: Computer science, CUDA, Fast multipole method, GPU cluster, MPI, N-body simulation, nVidia, Programming techniques, Tesla S1070

November 27, 2010 by hgpu

An Extension of the StarSs Programming Model for Platforms with Multiple GPUs

Eduard Ayguade, Rosa Badia, Francisco Igual, Jesus Labarta, Rafael Mayo, Enrique Quintana-Orti

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Tags: Algorithms, Computer science, CUDA, nVidia, Tesla S1070

November 27, 2010 by hgpu

Quantum computer simulation using the CUDA programming model

Eladio Gutierrez, Sergio Romero, Maria A. Trenas, Emilio L. Zapata

Tags: Computer science, CUDA, nVidia, Quantum computing

November 27, 2010 by hgpu

Predictive Runtime Code Scheduling for Heterogeneous Architectures

Victor Jimenez, Lluis Vilanova, Isaac Gelado, Marisa Gil, Grigori Fursin, Nacho Navarro

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8600 GTS, Task scheduling

November 27, 2010 by hgpu

CFAL-bench

Comparing Parallel Functional Array Languages: Programming and Performance

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

Can Large Language Models Predict Parallel Code Performance?

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

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

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high performance computing on graphics processing units: hgpu.org

Programming

An emotionally biased ant colony algorithm for pathfinding in games

Fast Conjugate Gradients with Multiple GPUs

Particle-Based Multiple Irregular Volume Rendering on CUDA

A Note on Auto-tuning GEMM for GPUs

Modeling of tsunami waves and atmospheric swirling flows with graphics processing unit

Accelerating Lattice Boltzmann Fluid Flow Simulations Using Graphics Processors

Accelerating geoscience and engineering system simulations on graphics hardware

Simulation of Shallow-Water systems using Graphics Processing Units

A massively parallel adaptive fast-multipole method on heterogeneous architectures

An Extension of the StarSs Programming Model for Platforms with Multiple GPUs

Quantum computer simulation using the CUDA programming model

Predictive Runtime Code Scheduling for Heterogeneous Architectures

Recent source codes

CFAL-bench

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

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

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

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