high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

Tile-based Lightweight Integer Compression in GPU

Anil Shanbhag, Bobbi W. Yogatama, Xiangyao Yu, Samuel Madden

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, nVidia V100, Package

July 16, 2023 by hgpu

Miriam: Exploiting Elastic Kernels for Real-time Multi-DNN Inference on Edge GPU

Zhihe Zhao, Neiwen Ling, Nan Guan, Guoliang Xing

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Tags: Benchmarking, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce RTX 2060, nVidia Jetson TX2

July 16, 2023 by hgpu

Improving the Performance, Portability, and Productivity of Hardware Accelerators

Pablo Antonio Martínez Sánchez

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, Matrix multiplication, Neural networks, nVidia, nVidia GeForce RTX 2080, nVidia GeForce RTX 2080 Ti, Performance, performance portability, Thesis

July 16, 2023 by hgpu

Safe, Seamless, And Scalable Integration Of Asynchronous GPU Streams In PETSc

Jacob Faibussowitsch, Mark F. Adams, Richard Tran Mills, Stefano Zampini, Junchao Zhang

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Tags: Computer science, CUDA, nVidia, nVidia A100, Package, Performance

July 9, 2023 by hgpu

Optimization Techniques for GPU Programming

Pieter Hijma, Stijn Heldens, Alessio Sclocco, Ben van Werkhoven, Henri E. Bal

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Tags: Computer science, CUDA, nVidia, OpenCL, Performance, survey

July 9, 2023 by hgpu

Matrix Multiplication Using Only Addition

Daniel Cussen, Jeffrey D. Ullman

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Tags: Algorithms, Computer science, Matrix multiplication

July 9, 2023 by hgpu

Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel Generation

William F. Godoy, Pedro Valero-Lara, Keita Teranishi, Prasanna Balaprakash, Jeffrey S. Vetter

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Tags: AI, Artificial intelligence, Benchmarking, Code generation, Computer science, CUDA, Fortran, HPC, Julia, nVidia, OpenACC, OpenMP, Package, Python

July 2, 2023 by hgpu

Out-of-the-box library support for DBMS operations on GPUs

Harish Kumar Harihara Subramanian, Bala Gurumurthy, Gabriel Campero Durand, David Broneske, Gunter Saake

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Tags: Computer science, Databases, Hashing, Heterogeneous systems, nVidia, nVidia GeForce RTX 2080 Ti, nVidia V100, OpenCL, Package, Performance

July 2, 2023 by hgpu

cuSLINK: Single-linkage Agglomerative Clustering on the GPU

Corey J. Nolet, Divye Gala, Alex Fender, Mahesh Doijade, Joe Eaton, Edward Raff, John Zedlewski, Brad Rees, Tim Oates

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Tags: Algorithms, Cluster analysis, Clustering, Computer science, CUDA, Hierarchical clustering, Machine learning, Nearest neighbour, nVidia, nVidia A100, nVidia DGX-1, Package

July 2, 2023 by hgpu

Managing, Profiling, and Optimizing Heterogeneous GPU Workloads

James Gleeson

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Tags: Computer science, CUDA, Heterogeneous systems, Neural networks, nVidia, nVidia GeForce GTX 480, nVidia GeForce RTX 2080 Ti, nVidia Grid K1, Optimization, Package, Performance, Tesla V100, Thesis, Virtualization

July 2, 2023 by hgpu

Deep Language Models for Software Testing and Optimisation

Foivos Tsimpourlas

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Tags: Benchmarking, Computer science, Deep learning, nVidia, nVidia GeForce GTX 1080, nVidia GeForce Titan X, OpenCL, Package, Software Engineering, Thesis

June 25, 2023 by hgpu

Compilation and Design Space Exploration of Dataflow Programs for Heterogeneous CPU-GPU Platforms

Aurélien François Gilbert Bloch

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Tags: Compilers, Computer science, CUDA, Design space exploration, DSP, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 1660, nVidia GeForce RTX 3080 Ti, Package, Thesis

June 25, 2023 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

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high performance computing on graphics processing units: hgpu.org

Programming

Tile-based Lightweight Integer Compression in GPU

Miriam: Exploiting Elastic Kernels for Real-time Multi-DNN Inference on Edge GPU

Improving the Performance, Portability, and Productivity of Hardware Accelerators

Safe, Seamless, And Scalable Integration Of Asynchronous GPU Streams In PETSc

Optimization Techniques for GPU Programming

Matrix Multiplication Using Only Addition

Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel Generation

Out-of-the-box library support for DBMS operations on GPUs

cuSLINK: Single-linkage Agglomerative Clustering on the GPU

Managing, Profiling, and Optimizing Heterogeneous GPU Workloads

Deep Language Models for Software Testing and Optimisation

Compilation and Design Space Exploration of Dataflow Programs for Heterogeneous CPU-GPU Platforms

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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