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host device — Generic programming in Cuda

Thomas Mejstrik

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Tags: Computer science, CUDA, nVidia, Programming Languages

September 17, 2023 by hgpu

Unified Shared Memory: Friend or Foe?

Juan Fumero Alfonso, Florin-Gabriel Blanaru, Athanasios Stratikopoulos, Steve Dohrmann, Sandhya Viswanathan, Christos-Efthymios Kotselidis

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Tags: Code generation, Computer science, CUDA, FPGA, Heterogeneous systems, Java, Memory, nVidia, nVidia GeForce RTX 3070, OpenCL

September 17, 2023 by hgpu

Scope is all you need: Transforming LLMs for HPC Code

Tal Kadosh, Niranjan Hasabnis, Vy A. Vo, Nadav Schneider, Neva Krien, Abdul Wasay, Nesreen Ahmed, Ted Willke, Guy Tamir, Yuval Pinter, Timothy Mattson, Gal Oren

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Tags: Code generation, Computer science, Deep learning, HPC, nVidia, nVidia A40, nVidia H100, OpenMP, Package

September 6, 2023 by hgpu

Leveraging Memory Copy Overlap for Efficient Sparse Matrix-Vector Multiplication on GPUs

Guangsen Zeng, Yi Zou

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia A40, Sparse matrix

September 6, 2023 by hgpu

Fortran High-Level Synthesis: Reducing the barriers to accelerating HPC codes on FPGAs

Gabriel Rodriguez-Canal, Nick Brown, Tim Dykes, Jessica R. Jones, Utz-Uwe Haus

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Tags: Computer science, Fortran, FPGA, HLS, HPC, OpenCL, Performance

September 6, 2023 by hgpu

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

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

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

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

See all packages

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high performance computing on graphics processing units: hgpu.org

host device — Generic programming in Cuda

Unified Shared Memory: Friend or Foe?

Scope is all you need: Transforming LLMs for HPC Code

Leveraging Memory Copy Overlap for Efficient Sparse Matrix-Vector Multiplication on GPUs

Fortran High-Level Synthesis: Reducing the barriers to accelerating HPC codes on FPGAs

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

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

Porting Batched Iterative Solvers onto Intel GPUs with SYCL

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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