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hgpu.org » Programming » CUDA

On a Simplified Approach to Achieve Parallel Performance and Portability Across CPU and GPU Architectures

Nathaniel Morgan, Caleb Yenusah, Adrian Diaz, Daniel Dunning,Jacob Moore,Erin Heilman, Calvin Roth, Evan Lieberman, Steven Walton, Sarah Brown, Daniel Holladay, Marko Knezevic, Gavin Whetstone, Zachary Baker, Robert Robey

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Tags: Computer science, CUDA, Fortran, HIP, nVidia, Package, performance portability, Pthreads

November 10, 2024 by hgpu

Over-synchronization in GPU Programs

Ajay Nayak, Arkaprava Basu

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Tags: Computer science, CUDA, nVidia, nVidia A100, nVidia GeForce RTX 3090, Package, Performance, PTX

November 10, 2024 by hgpu

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

Pascal Jahan Elahi

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Tags: Computer science, CUDA, MPI, nVidia, nVidia GH200, OpenMP, Package, Performance

November 10, 2024 by hgpu

NEO: Saving GPU Memory Crisis with CPU Offloading for Online LLM Inference

Xuanlin Jiang, Yang Zhou, Shiyi Cao, Ion Stoica, Minlan Yu

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Tags: Artificial intelligence, Computer science, CUDA, LLM, Memory, nVidia, nVidia A10, nVidia H100, Tesla T4

November 10, 2024 by hgpu

LLload: An Easy-to-Use HPC Utilization Tool

Chansup Byun, Albert Reuther, Julie Mullen, LaToya Anderson, William Arcand, Bill Bergeron, David Bestor, Alexander Bonn, Daniel Burrill, Vijay Gadepally, Michael Houle, Matthew Hubbell, Hayden Jananthan, Michael Jones, Piotr Luszczek, Peter Michaleas, Lauren Milechin, Guillermo Morales, Andrew Prout, Antonio Rosa, Charles Yee, Jeremy Kepner

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Tags: Computer science, CUDA, HPC, nVidia, Performance

November 3, 2024 by hgpu

Fastrack: Fast IO for Secure ML using GPU TEEs

Yongqin Wang, Rachit Rajat, Jonghyun Lee, Tingting Tang, Murali Annavaram

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Tags: Cloud, Computer science, CUDA, Machine learning, nVidia, nVidia H100, Security

October 27, 2024 by hgpu

General-Purpose Computing on Tensor Processors

Kuan-Chieh Hsu

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Tags: Artificial intelligence, Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce RTX 2080, nVidia GeForce RTX 3090, nVidia Jetson Nano, Package, Sparse matrix, Thesis, TPU

October 27, 2024 by hgpu

Using modern C++ to improve CUDA programs

Mythreya Kuricheti

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Tags: Computer science, CUDA, nVidia, nVidia Quadro RTX 5000, Performance, PTX, Thesis

October 27, 2024 by hgpu

Testing GPU Numerics: Finding Numerical Differences Between NVIDIA and AMD GPUs

Anwar Hossain Zahid, Ignacio Laguna, Wei Le

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Tags: AMD Radeon Instinct MI250, ATI, Computer science, CUDA, HIP, Numerical Analysis, nVidia, nVidia V100, Programming Languages

October 20, 2024 by hgpu

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Reza Abbasi, Sernam Lim

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Tags: AI, Artificial intelligence, Computer science, CUDA, LLM, Machine learning, Memory, nVidia, nVidia GeForce RTX 3090, nVidia Quadro RTX 8000, Package

October 20, 2024 by hgpu

Accelerating Drug Discovery in AutoDock-GPU with Tensor Cores

Gabin Schieffer, Ivy Peng

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Tags: Chemistry, Computer science, CUDA, Macromolecule, molecular docking, nVidia, nVidia A100, nVidia V100, Physics, Tesla T4

October 20, 2024 by hgpu

Optimized Code Generation for Parallel and Polyhedral Loop Nests using MLIR

Arun Thangamani

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Tags: AMD Radeon Instinct Mi50, ATI, Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia A100, OpenCL, Thesis

October 13, 2024 by hgpu

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

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

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