high performance computing on graphics processing units: hgpu.org

Clemens Grelck, Kevin Hammond, Heinz Hertlein, Philip Holzenspies, Chris Jesshope, Raimund Kirner, Bernd Scheuermann, Alex Shafarenko, Iraneus Te Boekhorst, Volkmar Wieser

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GT 425 M, Performance, Visualization

December 29, 2011 by hgpu

Monitoring Multiple Streams with Dynamic Time Warping using Graphic Processors

Jason Chang, Mi-Yen Yeh

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Data Structures and Algorithms, nVidia, Performance, Tesla C1060

December 28, 2011 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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

A class of communication-avoiding algorithms for solving general dense linear systems on CPU/GPU parallel machines

Block-asynchronous Multigrid Smoothers for GPU-accelerated Systems

Implementation of Kd-Trees on the GPU to Achieve Real Time Graphics Processing

A GPU Implementation of Inclusion-based Points-to Analysis

PARRAY: A Unifying Array Representation for Heterogeneous Parallelism

Efficient mapping of the training of Convolutional Neural Networks to a CUDA-based cluster

Automatic SIMD Code Generation

Extending a C-like Language for Portable SIMD Programming

Architecture-Aware Mapping and Optimization on a 1600-Core GPU

Process Time Comparison between GPU and CPU

Engineering Concurrent Software Guided by Statistical Performance Analysis