high performance computing on graphics processing units: hgpu.org

hgpu.org » nVidia Quadro NVS 295

Enabling OS Research by Inferring Interactions in the Black-Box GPU Stack

Konstantinos Menychtas, Kai Shen, Michael L. Scott

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 275, nVidia GeForce GTX 670, nVidia Quadro NVS 295, Performance

May 25, 2013 by hgpu

GPU Virtualization

Kristoffer Robin Stokke

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia Quadro NVS 295, Package, Python, Thesis, Virtualization

November 7, 2012 by hgpu

Real-time Visualization of Streaming Text with Force-Based Dynamic System

Jamal Alsakran, Yang Chen, Dongning Luo, Ye Zhao, Jing Yang, Wenwen Dou, Shixia Liu

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Tags: Computer science, CUDA, nVidia, nVidia Quadro NVS 295, Visualization

April 11, 2012 by hgpu

A Programmable Processing Array Architecture Supporting Dynamic Task Scheduling and Module-Level Prefetching

Junghee Lee, Hyung Gyu Lee, Soonhoi Ha, Jongman Kim, Chrysostomos Nicopoulos

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia Quadro NVS 295, Prefetch, Programming techniques, Task scheduling

April 5, 2012 by hgpu

Depth Estimation using Open Compute Language (OpenCL)

Giovanni Visentini, Amit Gupta

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Tags: Algorithms, Computational Complexity, Image processing, nVidia, nVidia Quadro NVS 295, OpenCL

April 4, 2012 by hgpu

Developing a CUDA solver for large sparse matrices for MARIN

Martijn de Jong

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Tags: Computer science, CUDA, Mathematics, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 580, nVidia Quadro NVS 295, Thesis

March 16, 2012 by hgpu

STREAMIT: Dynamic visualization and interactive exploration of text streams

Jamal Alsakran, Yang Chen, Ye Zhao, Jing Yang, Dongning Luo

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Tags: Computer science, CUDA, Interactive application, nVidia, nVidia Quadro NVS 295, Visualization

July 31, 2011 by hgpu

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

Enabling OS Research by Inferring Interactions in the Black-Box GPU Stack

GPU Virtualization

Real-time Visualization of Streaming Text with Force-Based Dynamic System

A Programmable Processing Array Architecture Supporting Dynamic Task Scheduling and Module-Level Prefetching

Depth Estimation using Open Compute Language (OpenCL)

Developing a CUDA solver for large sparse matrices for MARIN

STREAMIT: Dynamic visualization and interactive exploration of text streams

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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