high performance computing on graphics processing units: hgpu.org

Jacob Kahn, Vineel Pratap, Tatiana Likhomanenko, Qiantong Xu, Awni Hannun, Jeff Cai, Paden Tomasello, Ann Lee, Edouard Grave, Gilad Avidov, Benoit Steiner, Vitaliy Liptchinsky, Gabriel Synnaeve, Ronan Collobert

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Tags: Computer science, CUDA, Machine learning, nVidia, Package, Tesla V100

February 6, 2022 by hgpu

SZx: an Ultra-fast Error-bounded Lossy Compressor for Scientific Datasets

Xiaodong Yu, Sheng Di, Kai Zhao, jiannan Tian, Dingwen Tao, Xin Liang, Franck Cappello

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, nVidia A100, Tesla V100

February 6, 2022 by hgpu

Porting OpenACC to OpenMP on heterogeneous systems

Hichan Agueny

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Tags: Computer science, Heterogeneous systems, Laplace and Poisson equation, nVidia, OpenACC, Tesla P100

February 6, 2022 by hgpu

GC3: An Optimizing Compiler for GPU Collective Communication

Meghan Cowan, Saeed Maleki, Madanlal Musuvathi, Olli Saarikivi, Yifan Xiong

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Tags: Algorithms, Compilers, Computer science, CUDA, Machine learning, nVidia, nVidia A100

February 6, 2022 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

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

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

Experiences with implementing Kokkos’ SYCL backend

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

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high performance computing on graphics processing units: hgpu.org

A ML-based resource utilization OpenCL GPU-kernel fusion model

A Comprehensive Benchmark of Deep Learning Libraries on Mobile Devices

Lightning: Scaling the GPU Programming Model Beyond a Single GPU

Electrical-Level Attacks on CPUs, FPGAs, and GPUs: Survey and Implications in the Heterogeneous Era

Pattern-based Programming Abstractions for Heterogeneous Parallel Computing

The Ecological Footprint of Neural Machine Translation Systems

Improving Loop Parallelization by a Combination of Static and Dynamic Analyses in HLS

FC_ACCEL: Enabling Efficient, Low-Latency and Flexible Inference in DNN Fully Connected Layers, using Optimized Checkerboard Block matrix decomposition, fast scheduling, and a resource efficient 1D PE array with a custom HBM2 memory subsystem

Flashlight: Enabling Innovation in Tools for Machine Learning

SZx: an Ultra-fast Error-bounded Lossy Compressor for Scientific Datasets

Porting OpenACC to OpenMP on heterogeneous systems

GC3: An Optimizing Compiler for GPU Collective Communication

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

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

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

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