high performance computing on graphics processing units: hgpu.org

Pablo F. Zubieta Rico, Ludwig Schneider, Gustavo Perez-Lemus, Riccardo Alessandri, Siva Dasetty, Cintia A. Menéndez, Yiheng Wu, Yezhi Jin, Trung Nguyen, John Parker, Andrew L. Ferguson, Juan J. de Pablo

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Tags: Biology, Chemistry, Computational Physics, CUDA, Molecular dynamics, nVidia, Package, Physics, Python, Tesla V100

January 22, 2023 by hgpu

Assessing Opportunities of SYCL and Intel oneAPI for Biological Sequence Alignment

Manuel Costanzo, Enzo Rucci, Carlos García Sánchez, Marcelo Naiouf, Manuel Prieto-Matías

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Tags: Bioinformatics, Biology, Computational biology, Computer science, CUDA, Heterogeneous systems, Intel, Intel UHD 630, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980, nVidia GeForce RTX 2070, nVidia GeForce RTX 3090, OpenCL, Sequence alignment, SYCL, Tesla V100

November 27, 2022 by hgpu

Performance Study of GPU-based Joins

Efficiently Processing Large Relational Joins on GPUs

GenVectorX: A performance-portable SYCL library for Lorentz Vectors operations

bib boi: Tools to help with LaTeX paper writing

Compiler-centric across-stack deep learning acceleration

Kernel Tuner

Testing and Mutation Testing for GPU Kernels

CuPBoP-AMD: Extending CUDA to AMD Platforms

Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C+

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high performance computing on graphics processing units: hgpu.org

Applications

Accelerating bioinformatics applications on CUDA-enabled multi-GPU systems

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

Experience Migrating OpenCL to SYCL: A Case Study on Searches for Potential Off-Target Sites of Cas9 RNA-Guided Endonucleases on AMD GPUs

Comparing Performance and Portability between CUDA and SYCL for Protein Database Search on NVIDIA, AMD, and Intel GPUs

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

EfficientBioAI: Making Bioimaging AI Models Efficient in Energy, Latency and Representation

Genomics-GPU: A Benchmark Suite for GPU-accelerated Genome Analysis

Improving Performance of Hardware Accelerators by Optimizing Data Movement: A Bioinformatics Case Study

SaLoBa: Maximizing Data Locality and Workload Balance for Fast Sequence Alignment on GPUs

PySAGES: flexible, advanced sampling methods accelerated with GPUs

Assessing Opportunities of SYCL and Intel oneAPI for Biological Sequence Alignment

Recent source codes

Performance Study of GPU-based Joins

GenVectorX: A performance-portable SYCL library for Lorentz Vectors operations

bib boi: Tools to help with LaTeX paper writing

Kernel Tuner

CuPBoP-AMD: Extending CUDA to AMD Platforms

gossip: Efficient Communication Primitives for Multi-GPU Systems

GT4Py: GridTools for Python

miniBUDE: A BUDE virtual-screening benchmark, in many programming models

AUCMEDI: a framework for Automated Classification of Medical Images

Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C+

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