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A Symbolic Emulator for Shuffle Synthesis on the NVIDIA PTX Code

Kazuaki Matsumura, Simon Garcia De Gonzalo, Antonio J. Peña

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Tags: Benchmarking, Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan X, OpenACC, Package, PTX, Tesla K40, Tesla K80, Tesla V100

February 5, 2023 by hgpu

GPU-based Private Information Retrieval for On-Device Machine Learning Inference

Maximilian Lam, Jeff Johnson, Wenjie Xiong, Kiwan Maeng, Udit Gupta, Minsoo Rhu, Hsien-Hsin S. Lee, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks, Edward Suh

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Tags: Computer science, Information Retrieval, Machine learning, nVidia, nVidia V100, Security

January 29, 2023 by hgpu

Implementation of a motion estimation algorithm for Intel FPGAs using OpenCL

Manuel de Castro, Roberto R. Osorio, David L. Vilariño, Arturo Gonzalez-Escribano, Diego R. Llanos

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Tags: Computer science, FPGA, OpenCL, Package

January 29, 2023 by hgpu

Fast Merge Tree Computation via SYCL

Arnur Nigmetov, Dmitriy Morozov

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Tags: Computational Geometry, Computer science, nVidia, nVidia GeForce RTX 2080 Ti, OpenMP, Package, SYCL

January 29, 2023 by hgpu

Efficient OpenCL system integration of non-blocking FPGA accelerators

Topi Leppänen, Atro Lotvonen, Panagiotis Mousouliotis, Joonas Multanen, Georgios Keramidas, Pekka Jääskeläinen

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Tags: Computer science, FPGA, Heterogeneous systems, OpenCL, Package

January 22, 2023 by hgpu

PIGEON: Optimizing CUDA Code Generator for End-to-End Training and Inference of Relational Graph Neural Networks

Kun Wu, Mert Hidayetoğlu, Xiang Song, Sitao Huang, Da Zheng, Israt Nisa, Wen-mei Hwu

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, Neural networks, nVidia, nVidia GeForce RTX 3090

January 22, 2023 by hgpu

Analyzing Resource Utilization in an HPC System: A Case Study of NERSC’s Perlmutter

Jie Li, George Michelogiannakis, Brandon Cook, Dulanya Cooray, Yong Chen

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Tags: Computer science, HPC, nVidia, nVidia A100, Performance

January 22, 2023 by hgpu

AutoDDL: Automatic Distributed Deep Learning with Asymptotically Optimal Communication

Jinfan Chen, Shigang Li, Ran Gun, Jinhui Yuan, Torsten Hoefler

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Tags: Computer science, CUDA, Deep learning, Distributed computing, nVidia, nVidia A100, Package, Tesla P100

January 22, 2023 by hgpu

A Programming Model for GPU Load Balancing

Muhammad Osama, Serban D. Porumbescu, John D. Owens

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Tags: Algorithms, Computer science, CUDA, load balancing, nVidia, Package, Tesla V100

January 15, 2023 by hgpu

Improving the scalability of modern applications by parallel multi-core and many-core programming

Alessandro Borione

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce RTX 3070, OpenCL, Thesis

January 15, 2023 by hgpu

Distributed Calculations with Algorithmic Skeletons for Heterogeneous Computing Environments

Nina Herrmann, Herbert Kuchen

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Tags: Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, nVidia GeForce GTX 750 Ti, nVidia GeFroce RTX 2080 Ti, nVidia Quadro K620

January 15, 2023 by hgpu

OpenMP Advisor

Alok Mishra, Abid M. Malik, Meifeng Lin, Barbara Chapman

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Tags: AMD Radeon Instinct Mi50, ATI, Benchmarking, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce RTX 2080, OpenMP, Tesla A100, Tesla K80, Tesla V100

January 15, 2023 by hgpu

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

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

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high performance computing on graphics processing units: hgpu.org

A Symbolic Emulator for Shuffle Synthesis on the NVIDIA PTX Code

GPU-based Private Information Retrieval for On-Device Machine Learning Inference

Implementation of a motion estimation algorithm for Intel FPGAs using OpenCL

Fast Merge Tree Computation via SYCL

Efficient OpenCL system integration of non-blocking FPGA accelerators

PIGEON: Optimizing CUDA Code Generator for End-to-End Training and Inference of Relational Graph Neural Networks

Analyzing Resource Utilization in an HPC System: A Case Study of NERSC’s Perlmutter

AutoDDL: Automatic Distributed Deep Learning with Asymptotically Optimal Communication

A Programming Model for GPU Load Balancing

Improving the scalability of modern applications by parallel multi-core and many-core programming

Distributed Calculations with Algorithmic Skeletons for Heterogeneous Computing Environments

OpenMP Advisor

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

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

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