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Optimizing memory management on heterogeneous systems using polyhedral, compile-time techniques

Vassilis Vassiliadis

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Tags: Computer science, Heterogeneous systems, Memory model, OpenCL, Package, Thesis

August 7, 2014 by hgpu

Dense Arithmetic over Finite Fields with the CUMODP Library

Sardar Anisul Haquen, Xin Li, Farnam Mansouri, Marc Moreno Maza, Wei Pan, Ning Xie

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Tags: Algorithms, Computer science, CUDA, FFT, Linear Algebra, Mathematics, nVidia, Package, Tesla C2050

August 7, 2014 by hgpu

GIS Polygon Overlay Processing: New Parallel Algorithm and System Prototype

Satish Puri, Sushil K. Prasad

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Tags: Algorithms, Computer science, CUDA, Electronic design automation, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 780, Package

August 5, 2014 by hgpu

Scalable and High Performance Betweenness Centrality on the GPU

Adam McLaughlin, David A. Bader

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Tags: Algorithms, Computer science, CUDA, Graph theory, Numerical simulation, nVidia, nVidia GeForce GTX Titan, Package, Tesla M2090

August 1, 2014 by hgpu

A CUDA-Based Real Parameter Optimization Benchmark

Ke Ding, Ying Tan

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 560 Ti, Optimization, Package

July 30, 2014 by hgpu

Parallel Variable Pre-Selection and Lookahead Solving on GPUs

Christopher Schuster

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan, Package, SAT

July 16, 2014 by hgpu

CUD@SAT: SAT Solving on GPUs

Alessandro Dal Pal'u, Agostino Dovier, Andrea Formisano, Enrico Pontelli

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Tags: Computer science, CUDA, Numerical simulation, nVidia, nVidia GeForce GTS 450, nVidia GeForce GTX 560, Package, SAT, Tesla C2075

July 15, 2014 by hgpu

Benchmarking the Memory Hierarchy of Modern GPUs

Xinxin Mei, Kaiyong Zhao, Chengjian Liu, Xiaowen Chu

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Tags: Benchmarking, Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 560 Ti, nVidia GeForce GTX 780, Package, Performance

July 14, 2014 by hgpu

Combining Data Parallelism and Task Parallelism for Efficient Performance on Hybrid CPU and GPU Systems

Aditya Deshpande

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Tags: Algorithms, Compression, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 580, nVidia Quadro FX 3700, Package, Sorting, Sparse matrix, Tesla K20, Thesis

July 11, 2014 by hgpu

A Hybrid Parallel Implementation of the Aho-Corasick and Wu-Manber Algorithms Using NVIDIA CUDA and MPI Evaluated on a Biological Sequence Database

Charalampos S. Kouzinopoulos, John-Alexander M. Assael, Themistoklis K. Pyrgiotis, Konstantinos G. Margaritis

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Tags: Algorithms, Computer science, CUDA, Databases, GPU cluster, MPI, nVidia, nVidia GeForce GT 240, Package, Tesla S1070

July 11, 2014 by hgpu

Utilizing state-of-art NeuroES and GPGPU to optimize Mario AI

Hasse Lovgren

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Tags: ATI, ATI Radeon HD 5870, Computer science, Mathematics, Neural networks, nVidia, nVidia GeForce GTX 580, OpenCL, Package, Performance, Tesla C1060, Thesis

July 9, 2014 by hgpu

Latency considerations of depth-first GPU ray tracing

M. Guthe

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Tags: 3D Graphics and Realism, Computer science, CUDA, Image generation, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, Package, Raytracing

July 7, 2014 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

Applications

Optimizing memory management on heterogeneous systems using polyhedral, compile-time techniques

Dense Arithmetic over Finite Fields with the CUMODP Library

GIS Polygon Overlay Processing: New Parallel Algorithm and System Prototype

Scalable and High Performance Betweenness Centrality on the GPU

A CUDA-Based Real Parameter Optimization Benchmark

Parallel Variable Pre-Selection and Lookahead Solving on GPUs

CUD@SAT: SAT Solving on GPUs

Benchmarking the Memory Hierarchy of Modern GPUs

Combining Data Parallelism and Task Parallelism for Efficient Performance on Hybrid CPU and GPU Systems

A Hybrid Parallel Implementation of the Aho-Corasick and Wu-Manber Algorithms Using NVIDIA CUDA and MPI Evaluated on a Biological Sequence Database

Utilizing state-of-art NeuroES and GPGPU to optimize Mario AI

Latency considerations of depth-first GPU ray tracing

Recent source codes

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

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

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

Bandicoot: C++ library for GPU accelerated linear algebra

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

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

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

SIGMo: Scalable Isomorphism Graph Matching on GPUs

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

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