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CuPBoP-AMD: Extending CUDA to AMD Platforms

Jun Chen, Xule Zhou, Hyesoon Kim

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Tags: AMD Radeon Instinct MI210, ATI, Code generation, Computer science, CUDA, HIP, nVidia, OpenCL, Package

December 3, 2023 by hgpu

Evaluation of FPGA-based high performance computing platforms

Martin Frick-Lundgren

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Tags: Computer science, FPGA, HPC, Intel, Intel UHD 630, Matrix multiplication, OpenCL, Package, SYCL, Thesis

November 27, 2023 by hgpu

GPU Auto-tuning Framework for Optimal Performance and Power Consumption

Sunbal Cheema, Gul N. Khan

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Tags: Computer science, Energy-efficient computing, OpenCL

November 19, 2023 by hgpu

AFOCL: Portable OpenCL Programming of FPGAs via Automated Built-in Kernel Management

Topi Leppanen, Joonas Multanen, Leevi Leppänen, Pekka Jääskeläinen

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Tags: Computer science, FPGA, OpenCL, Package, performance portability

November 19, 2023 by hgpu

On the Three P’s of Parallel Programming for Heterogeneous Computing: Performance, Productivity, and Portability

Atharva Gondhalekar, Wu-chun Feng

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Tags: Computer science, FPGA, Heterogeneous systems, HLS, nVidia, nVidia GeForce RTX 3090, oneAPI, OpenCL, Performance, performance portability, SYCL

November 12, 2023 by hgpu

An Evaluation of Directive-Based Parallelization on the GPU Using a Parboil Benchmark

Jovan Ðukic, Marko Mišic

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce RTX 3080 Ti, OpenACC, OpenCL, OpenMP

November 12, 2023 by hgpu

Applying the Midas Touch of Reproducibility to High-Performance Computing

A. C. Minor, W. Feng

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Tags: Computer science, CUDA, Heterogeneous systems, HPC, nVidia, OpenCL, SYCL

November 5, 2023 by hgpu

A Comparison of the Performance of the Molecular Dynamics Simulation Package GROMACS Implemented in the SYCL and CUDA Programming Models

Leonard Apanasevich, Yogesh Kale, Himanshu Sharma, Ana Marija Sokovic

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Tags: Benchmarking, Bioinformatics, Biology, Chemistry, Computer science, CUDA, Heterogeneous systems, Molecular dynamics, nVidia, nVidia A100, nVidia P100, nVidia V100, OpenCL, OpenMP, Performance, SYCL

November 5, 2023 by hgpu

OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials

Peter Eastman, Raimondas Galvelis, Raúl P. Peláez, Charlles R. A. Abreu, Stephen E. Farr, Emilio Gallicchio, Anton Gorenko, Michael M. Henry, Frank Hu, Jing Huang, Andreas Krämer, Julien Michel, Joshua A. Mitchell, Vijay S. Pande, João PGLM Rodrigues, Jaime Rodriguez-Guerra, Andrew C. Simmonett, Jason Swails, Ivy Zhang, John D. Chodera, Gianni De Fabritiis, Thomas E. Markland

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Tags: AMD Radeon Pro V620, ATI, Chemical Physics, CUDA, HIP, Machine learning, Molecular dynamics, Molecular simulation, nVidia, nVidia A100, nVidia GeForce RTX 4080, OpenCL, Package, Physics

October 15, 2023 by hgpu

Strega: An HTTP Server for FPGAs

Fabio Maschi, Gustavo Alonso

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Tags: Computer science, FPGA, OpenCL, Package

October 15, 2023 by hgpu

Automated Buffer Sizing of Dataflow Applications in a High-Level Synthesis Workflow

Alexandre Honorat, Mickaël Dardaillon, Hugo Miomandre, Jean-François Nezan

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Tags: Code generation, Computer science, FPGA, HLS, OpenCL, Package, Performance

October 8, 2023 by hgpu

Impacts of Parallel Programming on Limited-Resource Hardware

Renato Barreto Hoffmann Filho

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Tags: Computer science, CUDA, nVidia, OpenCL, Programming techniques, Thesis

October 8, 2023 by hgpu

CFAL-bench

Comparing Parallel Functional Array Languages: Programming and Performance

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Efficient deep learning inference on end devices

Ouroboros: Virtualized Queues for dynamic memory management

Dynamic Memory Management on GPUs with SYCL

MSCCL++: A GPU-driven communication stack for scalable AI applications

MSCCL++: Rethinking GPU Communication Abstractions for Cutting-edge AI Applications

Benchmark compute shader of Unity against InteropUnityCUDA

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

Data-efficient LLM Fine-tuning for Code Generation

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

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