high performance computing on graphics processing units: hgpu.org

Thomas C.P. Chau, Maciej Kurek, James S. Targett, Jake Humphrey, George Skouroupathis, Alison Eele, Jan Maciejowski, Benjamin Cope, Kathryn Cobden, Philip Leong, Peter Y.K. Cheung, Wayne Luk

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Tags: Algorithms, Computer science, CUDA, FPGA, Machine learning, nVidia, Package, Tesla C2070

May 29, 2014 by hgpu

GASPP: A GPU-Accelerated Stateful Packet Processing Framework

Giorgos Vasiliadis, Lazaros Koromilas, Michalis Polychronakis, Sotiris Ioannidis

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Security

May 26, 2014 by hgpu

Automatic Termination Analysis for GPU Kernels

Jeroen Ketema, Alastair F. Donaldson

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

May 26, 2014 by hgpu

Efficient Algorithm for RSA Text Encryption Using CUDA-C

Sonam Mahajan, Maninder Singh

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 630 M, Security

May 26, 2014 by hgpu

A Parallel Jacobi-Type Lattice Basis Reduction Algorithm

Filip Jeremic, Sanzheng Qiao

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 660

May 26, 2014 by hgpu

GPU Passthrough Performance: A Comparison of KVM, Xen, VMWare ESXi, and LXC for CUDA and OpenCL Applications

John Paul Walters, Andrew J. Younge, Dong-In Kang, Ke-Thia Yao, Mikyung Kang, Stephen P. Crago, Geoffrey C. Fox

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Tags: Cloud, Computer science, CUDA, nVidia, OpenCL, Tesla C2075, Tesla K20, Virtualization

May 26, 2014 by hgpu

GPU vs FPGA: A Comparative Analysis for Non-standard Precision

Umar Ibrahim Minhas, Samuel Bayliss, George A. Constantinides

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Tags: Algorithms, Computer science, CUDA, Extended precision, FPGA, nVidia, Tesla C1060

May 25, 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Unified Particle Physics for Real-Time Applications

Data Layout Optimization for Multi-Valued Containers in OpenCL

Parallel Distance Threshold Query Processing for Spatiotemporal Trajectory Databases on the GPU

Simulating of query processing on multiprocessor database systems with modern coprocessors

Heterogeneous Computing for Solving System of the Linear Equations by the Conjugate Gradient Method

SMCGen: Generating Reconfigurable Design for Sequential Monte Carlo Applications

GASPP: A GPU-Accelerated Stateful Packet Processing Framework

Automatic Termination Analysis for GPU Kernels

Efficient Algorithm for RSA Text Encryption Using CUDA-C

A Parallel Jacobi-Type Lattice Basis Reduction Algorithm

GPU vs FPGA: A Comparative Analysis for Non-standard Precision

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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