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A Framework for Automated Performance Tuning and Code Verification on GPU Computing Platforms

Allison S. Gehrke, Ilkyeun Ra, Daniel A. Connors

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Tags: Code generation, Computer science, Numerical simulation, nVidia, Optimization, Performance, PTX

October 5, 2011 by hgpu

An Execution Model and Runtime For Heterogeneous Many-Core Systems

Gregory Diamos

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, Optimization, Package, PTX, Tesla C1060, Tesla S870, Thesis

October 2, 2011 by hgpu

Exploring The Latency and Bandwidth Tolerance of CUDA Applications

Gregory Diamos, Sudnya Padalikar

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Tags: Benchmarking, Computer science, CUDA, GPU cluster, Memory, nVidia, Performance, PTX, Tesla C1060

September 30, 2011 by hgpu

A PTX Code Generator for LLVM

Helge Rhodin

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, Optimization, PTX, Thesis, Virtualization

September 30, 2011 by hgpu

FATSEA-An Architectural Simulator for General Purpose Computing on GPUs

K.E. Ostby, J.L. Aragon, J.M. Garcia, M. Ujaldon

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Tags: Compilers, Computer science, CUDA, nVidia, Performance, PTX, Tesla C870

September 30, 2011 by hgpu

Translating GPU binaries to tiered SIMD architectures with Ocelot

Gregory Diamos, Andrew Kerr, Mukil Kesavan

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Tags: Algorithms, Cell processor, Compilers, Computer science, nVidia, PTX

September 30, 2011 by hgpu

Evolving CUDA PTX programs by quantum inspired linear genetic programming

Leandro F. Cupertino, Cleomar P. Silva, Douglas M. Dias, Marco Aurelio C. Pacheco, Cristiana Bentes

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Tags: Computer science, CUDA, Databases, Genetic programming, nVidia, Performance, PTX, Tesla C1060

September 29, 2011 by hgpu

LLVM to PTX Backend

Marco Keller

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, PTX

September 26, 2011 by hgpu

High-level GPU computing with jacket for MATLAB and C/C++

Gallagher Pryor, Brett Lucey, Sandeep Maddipatla, Chris McClanahan, John Melonakos, Vishwanath Venugopalakrishnan, Krunal Patel, Pavan Yalamanchili, James Malcolm

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Tags: Computer science, CUDA, FFT, Image processing, Linear Algebra, nVidia, nVidia GeForce 9600, nVidia GeForce GTX 480, nVidia GeForce GTX 580, OpenGL, Package, PTX, Tesla C1060, Tesla C2070

September 26, 2011 by hgpu

Identifying scalar behavior in CUDA kernels

Sylvain Collange

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Tags: Benchmarking, Code generation, Compilers, Computer science, CUDA, nVidia, PTX

September 26, 2011 by hgpu

Improving SIMT Efficiency of Global Rendering Algorithms with Architectural Support for Dynamic Micro-Kernels

Michael Steffen, Joseph Zambreno

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia Quadro FX 5800, Performance, PTX, Rendering

September 23, 2011 by hgpu

OptiX: a general purpose ray tracing engine

Steven G. Parker, James Bigler, Andreas Dietrich, Heiko Friedrich, Jared Hoberock, David Luebke, David McAllister, Morgan McGuire, Keith Morley, Austin Robison, Martin Stich

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, nVidia GeForce GTX 485, nVidia Quadro FX 5800, PTX, Raytracing, Software Engineering

September 14, 2011 by hgpu

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

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

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

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

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

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

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