high performance computing on graphics processing units: hgpu.org

Md. Mostofa Ali Patwary, Nadathur Rajagopalan Satish, Narayanan Sundaram, Jialin Liu, Peter Sadowski, Evan Racah, Suren Byna, Craig Tull, Wahid Bhimji, Prabhat, Pradeep Dubey

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Tags: Algorithms, classification, Computer science, Data mining, Intel Xeon Phi, KD-tree, Machine learning, Nearest neighbour

July 30, 2016 by hgpu

Heterogeneous Computing for Data Stream Mining

Vladimir Petko

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Tags: Algorithms, Computer science, Data mining, Heterogeneous systems, Machine learning, Nearest neighbour, nVidia, OpenCL, Tesla C2050, Thesis

July 18, 2016 by hgpu

Accelerating Eulerian Fluid Simulation With Convolutional Networks

Jonathan Tompson, Kristofer Schlachter, Pablo Sprechmann, Ken Perlin

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Tags: 3D Graphics and Realism, CNN, Computational Complexity, CUDA, Deep learning, Fluid dynamics, Fluid simulation, Machine learning, nVidia, nVidia GeForce GTX Titan X

July 16, 2016 by hgpu

Deep Learning for Mortgage Risk

Justin Sirignano, Apaar Sadhwani, Kay Giesecke

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Tags: CUDA, Deep learning, Finance, Machine learning, Neural networks, nVidia, Statistical Finance

July 11, 2016 by hgpu

Torchnet: An Open-Source Platform for (Deep) Learning Research

Ronan Collobert, Laurens van der Maaten, Armand Joulin

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Tags: Computer science, CUDA, Deep learning, Lua, Machine learning, nVidia, Package, Torch

July 8, 2016 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

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high performance computing on graphics processing units: hgpu.org

Matrix Computations and Optimization in Apache Spark

Benchmarking State-of-the-Art Deep Learning Software Tools

Hybrid CPU-GPU Framework for Network Motifs

Learning Structured Sparsity in Deep Neural Networks

Iterative Hard Thresholding for Model Selection in Genome-Wide Association Studies

OpenCL-accelerated object classification in video streams using Spatial Pooler of Hierarchical Temporal Memory

RETURNN: The RWTH Extensible Training framework for Universal Recurrent Neural Networks

PANDA: Extreme Scale Parallel K-Nearest Neighbor on Distributed Architectures

Heterogeneous Computing for Data Stream Mining

Accelerating Eulerian Fluid Simulation With Convolutional Networks

Deep Learning for Mortgage Risk

Torchnet: An Open-Source Platform for (Deep) Learning Research

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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