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Quadratic Pseudo-Boolean Optimization for Scene Analysis using CUDA

Andreas Bauer

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Tags: Algorithms, Computer science, Computer vision, CUDA, Image reconstruction, nVidia, nVidia GeForce GTX 450 Ti, Thesis

February 13, 2015 by hgpu

Large-Scale Deep Learning on the YFCC100M Dataset

Karl Ni, Roger Pearce, Kofi Boakye, Brian Van Essen, Damian Borth, Barry Chen, Eric Wang

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Tags: Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, Tesla M2050

February 13, 2015 by hgpu

Primal Dual Affine Scaling on GPUs

Nithish Divakar

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Tags: Computer science, CUDA, Numerical Analysis, nVidia, Tesla S1070

February 13, 2015 by hgpu

FSCL: Homogeneous programming, scheduling and execution on heterogeneous platforms

Gabriele Cocco

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Source codes

Tags: ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, OpenCL, Package, Thesis

February 10, 2015 by hgpu

GPU-accelerated HMM for Speech Recognition

Leiming Yu, Yash Ukidave, David Kaeli

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Source codes

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, Package, Speech recognition

February 10, 2015 by hgpu

Analysis and Modeling of the Timing Behavior of GPU Architectures

Petros Voudouris

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, Thesis

February 10, 2015 by hgpu

Patterns and Rewrite Rules for Systematic Code Generation (From High-Level Functional Patterns to High-Performance OpenCL Code)

Michel Steuwer, Christian Fensch, Christophe Dubach

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Tags: ATI, ATI Radeon HD 7970, Code generation, Computer science, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Programming Languages

February 10, 2015 by hgpu

FIR filtering and AES encryption with OpenCL 2.0

Carter McCardwell, Tuan Dao, Saoni Mukherjee, David Kaeli

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Tags: AES, Computer science, Filtering, Heterogeneous systems, OpenCL, Security

February 9, 2015 by hgpu

Speech Recognition on Modern Graphic Processing Units

Leiming Yu, John Magrath, Ajey Pandey, Matthew Sears, David Kaeli

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Speech recognition

February 9, 2015 by hgpu

Fast Subgraph Matching on Large Graphs using Graphics Processors

Ha-Nguyen Tran, Jung-jae Kim, Bingsheng He

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Tesla C2050

February 9, 2015 by hgpu

Sparse Matrix-Vector Multiplication on GPU

Arash Ashari

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, Machine learning, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX Titan, Sparse matrix, Tesla K10, Thesis

February 9, 2015 by hgpu

Extending the Gotran framework: LATEX and GPU acceleration

George Bahijevitch Bahij

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Tags: Computational modelling, Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GT 650 M, nVidia GeForce GTX Titan, ODEs, Ordinary differential equations, Python, Thesis

February 6, 2015 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Quadratic Pseudo-Boolean Optimization for Scene Analysis using CUDA

Large-Scale Deep Learning on the YFCC100M Dataset

Primal Dual Affine Scaling on GPUs

FSCL: Homogeneous programming, scheduling and execution on heterogeneous platforms

GPU-accelerated HMM for Speech Recognition

Analysis and Modeling of the Timing Behavior of GPU Architectures

Patterns and Rewrite Rules for Systematic Code Generation (From High-Level Functional Patterns to High-Performance OpenCL Code)

FIR filtering and AES encryption with OpenCL 2.0

Speech Recognition on Modern Graphic Processing Units

Fast Subgraph Matching on Large Graphs using Graphics Processors

Sparse Matrix-Vector Multiplication on GPU

Extending the Gotran framework: LATEX and GPU acceleration

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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