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Improving GPU Performance by Regrouping CPU-Memory Data

Deepthi Gummadi

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Tags: ARM, Computer science, CUDA, nVidia, Performance, Tesla C2075, Tesla K20, Thesis

November 25, 2014 by hgpu

A Self-Optimizing Framework for Developing Metrology Software on Massive Parallel Processor Architectures

T. Beier

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Tags: Algorithms, ATI, ATI Radeon HD 7750, Computer science, nVidia, nVidia GeForce GTX 480, OpenCL, Performance

November 25, 2014 by hgpu

Scalable Verification Techniques for Data-Parallel Programs

Nathan Yong Seng Chong

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Tags: ARM, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 570, OpenCL, Package, Tesla M2050, Thesis

November 25, 2014 by hgpu

Using CUDA architecture for computer simulations of thermomechanical phenomena

Grzegorz Michalski, Norbert Sczygiol, Siergiei Leonov

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GT 200, Solidification

November 20, 2014 by hgpu

Automatic Performance Tuning of Pipeline Patterns for Heterogeneous Parallel Architectures

E. Bajrovic, S. Benkner

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Tags: Computer science, Heterogeneous systems, nVidia, OpenCL, OpenCV, Performance, Tesla C2050, Tesla K20

November 20, 2014 by hgpu

Processing Hard Sphere Collisions on a GPU Using OpenCL

Zachary Langbert, Mark C. Lewis

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Tags: ATI, ATI Radeon HD 7970, Collision detection, Computer science, nVidia, nVidia GeForce GTX 670, OpenCL

November 18, 2014 by hgpu

Glider: A GPU Library Driver for Improved System Security

Ardalan Amiri Sani, Lin Zhong, Dan S. Wallach

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Tags: ATI, ATI Radeon HD 6450, Computer science, OpenCL, OpenGL, Operating systems, Security

November 18, 2014 by hgpu

Mobile GPGPU Acceleration of Embodied Robot Simulation

Simon Jones, Matthew Studley, Alan Winfield

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Tags: Computer science, OpenCL, Package, Robotics

November 16, 2014 by hgpu

Ray Reordering Techniques for GPU Ray-Cast Ambient Occlusion

Vasco Costa, Joao M. Pereira, Joaquim A. Jorge

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce GTX Titan, OpenCL, Rendering

November 16, 2014 by hgpu

CUDArray: CUDA-based NumPy

Anders Boesen Lindbo Larsen

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Tags: Computer science, CUDA, Neural networks, nVidia, Package, Python

November 16, 2014 by hgpu

Whippletree: Task-based Scheduling of Dynamic Workloads on the GPU

Markus Steinberger, Michael Kenzel, Pedro Boechat, Bernhard Kerbl, Mark Dokter, Dieter Schmalstieg

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, Package, Rendering

November 13, 2014 by hgpu

Manycore processing of repeated range queries over massive moving objects observations

Francesco Lettich, Salvatore Orlando, Claudio Silvestri, Christian S. Jensen

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 560

November 13, 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

Improving GPU Performance by Regrouping CPU-Memory Data

A Self-Optimizing Framework for Developing Metrology Software on Massive Parallel Processor Architectures

Scalable Verification Techniques for Data-Parallel Programs

Using CUDA architecture for computer simulations of thermomechanical phenomena

Automatic Performance Tuning of Pipeline Patterns for Heterogeneous Parallel Architectures

Processing Hard Sphere Collisions on a GPU Using OpenCL

Glider: A GPU Library Driver for Improved System Security

Mobile GPGPU Acceleration of Embodied Robot Simulation

Ray Reordering Techniques for GPU Ray-Cast Ambient Occlusion

CUDArray: CUDA-based NumPy

Whippletree: Task-based Scheduling of Dynamic Workloads on the GPU

Manycore processing of repeated range queries over massive moving objects observations

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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