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PoCL-R: An Open Standard Based Offloading Layer for Heterogeneous Multi-Access Edge Computing with Server Side Scalability

Jan Solanti, Michal Babej, Julius Ikkala, Pekka Jääskeläinen

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Tags: Computer science, Distributed computing, Fluid dynamics, Heterogeneous systems, nVidia, nVidia GeForce RTX 2080 Ti, nVidia RTX A6000, OpenCL, Package, Rendering

September 6, 2023 by hgpu

HPAC-Offload: Accelerating HPC Applications with Portable Approximate Computing on the GPU

Zane Fink, Konstantinos Parasyris, Giorgis Georgakoudis, Harshitha Menon

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Tags: AMD Radeon Instinct MI250X, ATI, Code generation, Computer science, HPC, LLVM, nVidia, nVidia V100, OpenMP, Package

September 6, 2023 by hgpu

Compute units in OpenMP: Extensions for heterogeneous parallel programming

Marc Gonzàlez-Tallada, Enric Morancho

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Tags: AMD Radeon Instinct Mi50, ATI, Benchmarking, Computer science, Heterogeneous systems, OpenMP, Task scheduling

August 28, 2023 by hgpu

Performant low-order matrix-free finite element kernels on GPU architectures

Randolph R. Settgast, Yohann Dudouit, Nicola Castelletto, William R. Tobin, Benjamin C. Corbett, Sergey Klevtsov

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Tags: AMD Radeon Instinct MI250X, ATI, FEM, Finite element method, Mathematics, Numerical Analysis, nVidia, nVidia A100, nVidia V100, Package, Sparse

August 28, 2023 by hgpu

Sieve: Stratified GPU-Compute Workload Sampling

Mahmood Naderan-Tahan, Hossein SeyyedAghaei, Lieven Eeckhout

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Tags: Computer science, CUDA, nVidia, nVidia GeForce RTX 2080 Ti, nVidia GeForce RTX 3080, Package, Performance

August 28, 2023 by hgpu

Mashing load balancing algorithm to boost hybrid kernels in molecular dynamics simulations

Raúl Nozal, Jose Luis Bosque

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Tags: AMD Radeon RX 5700 XT, ATI, Computer science, Heterogeneous systems, HPC, Molecular dynamics, OpenCL, OpenMP, Package, performance portability

August 28, 2023 by hgpu

Novel insights on atomic synchronization for sort-based group-by on GPUs

Bala Gurumurthy, David Broneske, Martin Schäler, Thilo Pionteck

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Tags: Computer science, Databases, Hashing, Heterogeneous systems, nVidia, nVidia A100, nVidia GeForce GTX 1050 Ti, nVidia GeForce RTX 2080 Ti, nVidia V100, OpenCL, Package, Sorting

August 28, 2023 by hgpu

Quantifying OpenMP: Statistical Insights into Usage and Adoption

Tal Kadosh, Niranjan Hasabnis, Timothy Mattson, Yuval Pinter, Gal Oren

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Tags: Computer science, CUDA, Databases, Fortran, HPC, MPI, nVidia, OpenACC, OpenCL, OpenMP, Package, SYCL

August 20, 2023 by hgpu

Generating Parallel OpenCL and OpenMP Programs from Dataflow Graphs

Evelyn Borth

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Tags: Benchmarking, Code generation, Computer science, OpenCL, OpenMP, Thesis

August 20, 2023 by hgpu

Porting Batched Iterative Solvers onto Intel GPUs with SYCL

Phuong Nguyen, Pratik Nayak, Hartwig Anzt

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Tags: Computer science, CUDA, Intel, Intel Data Center GPU Max 1550, nVidia, nVidia A100, nVidia H100, Package, performance portability, Physics, SYCL

August 20, 2023 by hgpu

APACE: AlphaFold2 and advanced computing as a service for accelerated discovery in biophysics

Hyun Park, Parth Patel, Roland Haas, E. A. Huerta

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Tags: AI, Algorithms, Biology, Biomolecules, Biophysics, nVidia, nVidia A100, nVidia A40, Package

August 20, 2023 by hgpu

Increased reliability on Intel GPUs via software diverse redundancy

Nikolaos Andriotis

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Tags: Computer science, Deep learning, Machine learning, MPI, nVidia, OpenCL, Thesis

August 20, 2023 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

PoCL-R: An Open Standard Based Offloading Layer for Heterogeneous Multi-Access Edge Computing with Server Side Scalability

HPAC-Offload: Accelerating HPC Applications with Portable Approximate Computing on the GPU

Compute units in OpenMP: Extensions for heterogeneous parallel programming

Performant low-order matrix-free finite element kernels on GPU architectures

Sieve: Stratified GPU-Compute Workload Sampling

Mashing load balancing algorithm to boost hybrid kernels in molecular dynamics simulations

Novel insights on atomic synchronization for sort-based group-by on GPUs

Quantifying OpenMP: Statistical Insights into Usage and Adoption

Generating Parallel OpenCL and OpenMP Programs from Dataflow Graphs

Porting Batched Iterative Solvers onto Intel GPUs with SYCL

APACE: AlphaFold2 and advanced computing as a service for accelerated discovery in biophysics

Increased reliability on Intel GPUs via software diverse redundancy

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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