high performance computing on graphics processing units: hgpu.org

Ruibang Luo, Thomas Wong, Jianqiao Zhu, Chi-Man Liu, Edward Wu, Lap-Kei Lee, Haoxiang Lin, Wenjuan Zhu, David W. Cheung, Hing-Fung Ting, Siu-Ming Yiu, Chang Yu, Yingrui Li, Ruiqiang Li, Tak-Wah Lam

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Next-Generation sequencing, nVidia, Package, Tesla C2070, Tesla M2050

February 25, 2013 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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high performance computing on graphics processing units: hgpu.org

C Language Extensions for Hybrid CPU/GPU Programming with StarPU

A journey from single-GPU to optimized multi-GPU SPH with CUDA

CMCpy: Genetic Code-Message Coevolution Models in Python

High Performance Computing using GPGPU’s

How to Benefit from AMD, Intel and Nvidia Accelerator Technologies in Scilab

GRay: a Massively Parallel GPU-Based Code for Ray Tracing in Relativistic Spacetimes

Symbolic Crosschecking of Data-Parallel Floating Point Code

clMAGMA: High Performance Dense Linear Algebra with OpenCL

High Performance GPU Accelerated Local Optimization in TSP

OpenOF: Framework for Sparse Non-linear Least Squares Optimization on a GPU

Acceleration of the MMFF94 routines within OpenBabel using Eigen and OpenCL

SOAP3-dp: Fast, Accurate and Sensitive GPU-based Short Read Aligner

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