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Randomized selection on the GPU

Laura Monroe, Joanne Wendelberger, Sarah Michalak

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 285, nVidia Quadro FX 5000, nVidia Quadro FX 6000, Optimization, Presentation, Probability, Programming techniques

September 19, 2011 by hgpu

Hybrid smoothed particle hydrodynamics

Karthik Raveendran, Chris Wojtan, Greg Turk

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Tags: 3D Graphics and Realism, Algorithms, Computer science, Fluid simulation, Particle simulation

September 19, 2011 by hgpu

Simpler and faster HLBVH with work queues

Kirill Garanzha, Jacopo Pantaleoni, David McAllister

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Raytracing, Real-time graphics

September 19, 2011 by hgpu

A GPU-tailored approach for training kernelized SVMs

Andrew Cotter, Nathan Srebro, Joseph Keshet

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Tags: Algorithms, Clustering, Computer science, nVidia, Optimization, Package, Performance, Programming techniques, Tesla C1060

September 19, 2011 by hgpu

Stream computing on graphics hardware

Ian Buck

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Tags: Algorithms, ATI, ATI Radeon X800 XT, Benchmarking, Brook, Compilers, Computer science, nVidia, nVidia GeForce 6800, Review, Thesis

September 19, 2011 by hgpu

A small-world network model for distributed storage of semantic metadata

A. Leist, K. A. Hawick

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Tags: Artificial intelligence, Computer science, CUDA, Networks, nVidia

September 19, 2011 by hgpu

An adaptative game loop architecture with automatic distribution of tasks between CPU and GPU

Mark Joselli, Marcelo Zamith, Esteban Clua, Anselmo Montenegro, Regina Leal-Toledo, Aura Conci, Paulo Pagliosa, Luis Valente, Bruno Feijo

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Tags: Computer science, CUDA, Games, nVidia, nVidia GeForce 8200 M, nVidia GeForce 8400 GS, nVidia GeForce 8800 GTS, Performance, Task scheduling

September 19, 2011 by hgpu

Returning control to the programmer: SIMD intrinsics for virtual machines

Jonathan Parri, Daniel Shapiro, Miodrag Bolic, Voicu Groza

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Tags: Computer science, Java, Optimization, Programming Languages

September 16, 2011 by hgpu

NIMBLE: a toolkit for the implementation of parallel data mining and machine learning algorithms on mapreduce

Amol Ghoting, Prabhanjan Kambadur, Edwin Pednault, Ramakrishnan Kannan

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Tags: Algorithms, Computer science, Data mining, Machine learning, MapReduce, MPI, OpenCL, Performance, Software Engineering

September 16, 2011 by hgpu

Programmable and Scalable Architecture for Graphics Processing Units

Carlos S. de La Lama, Pekka Jaaskelainen, Jarmo Takala

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Tags: Computer science, GLSL, nVidia, nVidia GeForce 9400 M, OpenCL, OpenGL, Performance, Programming techniques

September 16, 2011 by hgpu

Searching for Concurrent Design Patterns in Video Games

Micah J. Best, Alexandra Fedorova, Ryan Dickie, Andrea Tagliasacchi, Alex Couture-Beil, Craig Mustard, Shane Mottishaw, Aron Brown, Zhi Feng Huang, Xiaoyuan Xu, Nasser Ghazali, Andrew Brownsword

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Tags: Algorithms, Computer science, Games, Performance

September 16, 2011 by hgpu

A Light-Weight Approach to Dynamical Runtime Linking Supporting Heterogenous, Parallel, and Reconfigurable Architectures

Rainer Buchty, David Kramer, Mario Kicherer, Wolfgang Karl

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Tags: Algorithms, Computer science, Heterogeneous systems, Programming techniques

September 16, 2011 by hgpu

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

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

SeedFold: Scaling Biomolecular Structure Prediction

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

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

BoltzGen:Toward Universal Binder Design

BoltzGen:Toward Universal Binder Design

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

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

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

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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