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The PEPPHER Approach to Programmability and Performance Portability for Heterogeneous many-core Architectures

Siegfried Benkner, Sabri Pllana, Jesper Larsson Traff, Philippas Tsigas, Andrew Richards, Raymond Namyst, Beverly Bachmayer, Christoph Kessler, David Moloney, Peter Sanders

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Optimization, Performance, Tesla C1060

February 8, 2012 by hgpu

Acceleration of a Locally Tuned Sine Non Linear Video Enhancement Algorithm on GPGPU

Julian Daniel John

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, Tesla C2070, Thesis

February 8, 2012 by hgpu

Symbolic Testing of OpenCL Code

Peter Collingbourne, Cristian Cadar, Paul H. J. Kelly

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Tags: Benchmarking, Code generation, Computer science, nVidia, OpenCL, Package, PTX, Tesla C1060

February 8, 2012 by hgpu

Verifiable Computation with Massively Parallel Interactive Proofs

Justin Thaler, Mike Roberts, Michael Mitzenmacher, Hanspeter Pfister

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Tags: Benchmarking, Cloud, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 480, Package, Security

February 8, 2012 by hgpu

GMP implementation on CUDA – A Backward Compatible Design With Performance Tuning

Hao Jun Liu, Chu Tong

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Tags: Algorithms, Computer science, CUDA, Elementary functions, nVidia, nVidia GeForce GTX 280, Performance, Security

February 7, 2012 by hgpu

Enabling Traceability in MDE to Improve Performance of GPU Applications

Antonio Wendell De Oliveira Rodrigues, Vincent Aranega, Anne Etien, Frederic Guyomarc'H, Jean-Luc Dekeyser

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Tags: Algorithms, Computer science, nVidia, OpenCL, Performance, Programming techniques, Tesla S1070

February 7, 2012 by hgpu

Stochastic Differential Equations simulation using GPU

Narayana Darapaneni, Prakalp Somawanshi, Meghana Joshi

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Tags: Algorithms, Computer science, CUDA, Differential equations, Finance, Monte Carlo simulation, nVidia, nVidia GeForce GTX 275, Pseudo-random number generators, Stochastic simulation

February 7, 2012 by hgpu

Aggregate Gaze Visualization with Real-time Heatmaps

Andrew T. Duchowski, Margaux M. Price, Miriah Meyer, Pilar Orero

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Tags: Algorithms, Computer science, GLSL, Image generation, nVidia, nVidia GeForce 8800 GT, nVidia GeForce 8800 GTX, nVidia GeForce 9400 M, OpenGL, Rendering, Visualization

February 7, 2012 by hgpu

Realistic Lighting Simulation for Interactive VR Applications

Alexander Loffler, Lukas Marsalek, Hilko Hoffmann, Philipp Slusallek

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce 9600 GT, OpenGL, Rasterization, Raytracing, Virtual reality

February 6, 2012 by hgpu

A Computational Model of Afterimages

Tobias Ritschel, Elmar Eisemann

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce GTX 480, OpenGL

February 6, 2012 by hgpu

A toolkit to describe and interactively display three-manifolds embedded in four-space

Don V. Black

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Tags: Algorithms, Computer science, OpenGL, Visualization

February 6, 2012 by hgpu

Comparing Linear and Convex Relaxations for Stereo and Motion

Thomas Schoenemann

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Tags: Algorithms, Computer science, Computer vision, nVidia, Optimization, Tesla C2050

February 5, 2012 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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high performance computing on graphics processing units: hgpu.org

The PEPPHER Approach to Programmability and Performance Portability for Heterogeneous many-core Architectures

Acceleration of a Locally Tuned Sine Non Linear Video Enhancement Algorithm on GPGPU

Symbolic Testing of OpenCL Code

GMP implementation on CUDA – A Backward Compatible Design With Performance Tuning

Enabling Traceability in MDE to Improve Performance of GPU Applications

Stochastic Differential Equations simulation using GPU

Aggregate Gaze Visualization with Real-time Heatmaps

Realistic Lighting Simulation for Interactive VR Applications

A Computational Model of Afterimages

A toolkit to describe and interactively display three-manifolds embedded in four-space

Comparing Linear and Convex Relaxations for Stereo and Motion

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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