nVidia Quadro FX 5600

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Interaction and Visualization Techniques for Immersive Exploration and Perception of 3D datasets

Nan Wang

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Tags: Computer science, nVidia, nVidia Quadro FX 5600, OpenGL, Rendering, Thesis, Virtual reality, Visualization

May 13, 2013 by hgpu

GPUWattch: Enabling Energy Optimizations in GPGPUs

Jingwen Leng, Tayler Hetherington, Ahmed ElTantawy, Syed Gilani, Nam Sung Kim, Tor M. Aamodt, Vijay Janapa Reddi

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, nVidia Quadro FX 5600, Performance

May 4, 2013 by hgpu

Improving GPU Performance Prediction with Data Transfer Modeling

Michael Boyer, Jiayuan Meng, Kalyan Kumaran

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Tags: Computer science, CUDA, nVidia, nVidia Quadro FX 5600, Performance

April 6, 2013 by hgpu

Dataflow-driven GPU performance projection for multi-kernel transformations

Jiayuan Meng, Vitali A. Morozov, Venkatram Vishwanath, Kalyan Kumaran

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Tags: Computer science, CUDA, nVidia, nVidia Quadro FX 5600, Performance, Tesla C1060

November 20, 2012 by hgpu

Effects of Compiler Optimizations in OpenMP to CUDA Translation

Amit Sabne, Putt Sakdhnagool, Rudolf Eigenmann

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia Quadro FX 5600, OpenMP, Optimization

May 6, 2012 by hgpu

OpenMPC: Extended OpenMP for Efficient Programming and Tuning on GPUs

Seyong Lee, Rudolf Eigenmann

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia Quadro FX 5600, OpenMP, Performance, Programming techniques

March 26, 2012 by hgpu

Plenoptic Rendering With Interactive Performance Using GPUs

Andrew Lumsdaine, Georgi Chunev, Todor Georgiev

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Tags: Algorithms, Image processing, nVidia, nVidia Quadro FX 5600, OpenGL, Rendering

January 21, 2012 by hgpu

Enhancing Performance for Solving Finite Element Mesh using Heterogeneous Platforms

Muhammad Hasan Jamal, Nabeel AlSaber

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Tags: Computer science, CUDA, FEM, Finite element method, Heterogeneous systems, Linear Algebra, nVidia, nVidia Quadro FX 5600

January 15, 2012 by hgpu

Memory-level and Thread-level Parallelism Aware GPU Architecture Performance Analytical Model

Sunpyo Hong, Hyesoon Kim

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Tags: Analytical model, Benchmarking, Computer science, CUDA, Memory level parallelism, nVidia, nVidia Quadro FX 5600, Warp level parallelism

December 15, 2011 by hgpu

GROPHECY: GPU performance projection from CPU code skeletons

Jiayuan Meng, Vitali A. Morozov, Kalyan Kumaran, Venkatram Vishwanath, Thomas D. Uram

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Tags: Analytical model, Benchmarking, Computer science, CUDA, nVidia, nVidia Quadro FX 5600, Performance, Tesla C1060

December 5, 2011 by hgpu

Heterogeneous Computing and Load Balancing Techniques for Monte Carlo Simulation in a Distributed Environment

Isha Sanjay Deshpande

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, Monte Carlo simulation, nVidia, nVidia Quadro FX 5600, Thesis

November 25, 2011 by hgpu

Accelerating Component-Based Dataflow Middleware with Adaptivity and Heterogeneity

Timothy D. R. Hartley

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro FX 5600, Optimization, Performance, Thesis

October 22, 2011 by hgpu

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

GSParLib: A multi-level programming interface unifying OpenCL and CUDA for expressing stream and data parallelism

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

A User’s Guide to KSig: GPU-Accelerated Computation of the Signature Kernel

IterApp: Iterative Application Skeleton

Boosting Performance of Iterative Applications on GPUs: Kernel Batching with CUDA Graphs

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

Data Parallel Visualization and Rendering on the RAMSES Supercomputer with ANARI

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

See all packages

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high performance computing on graphics processing units: hgpu.org

Interaction and Visualization Techniques for Immersive Exploration and Perception of 3D datasets

GPUWattch: Enabling Energy Optimizations in GPGPUs

Improving GPU Performance Prediction with Data Transfer Modeling

Dataflow-driven GPU performance projection for multi-kernel transformations

Effects of Compiler Optimizations in OpenMP to CUDA Translation

OpenMPC: Extended OpenMP for Efficient Programming and Tuning on GPUs

Plenoptic Rendering With Interactive Performance Using GPUs

Enhancing Performance for Solving Finite Element Mesh using Heterogeneous Platforms

Memory-level and Thread-level Parallelism Aware GPU Architecture Performance Analytical Model

GROPHECY: GPU performance projection from CPU code skeletons

Heterogeneous Computing and Load Balancing Techniques for Monte Carlo Simulation in a Distributed Environment

Accelerating Component-Based Dataflow Middleware with Adaptivity and Heterogeneity

Recent source codes

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

IterApp: Iterative Application Skeleton

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

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