high performance computing on graphics processing units: hgpu.org

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Machine-Learning-based Performance Heuristics for Runtime CPU/GPU Selection

Akihiro Hayashi, Kazuaki Ishizaki, Vivek Sarkar, Gita Koblents

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Tags: Code generation, Compilers, Computer science, CUDA, Java, Machine learning, nVidia, OpenCL, Tesla K40

October 27, 2015 by ahayashi

ZNN – A Fast and Scalable Algorithm for Training 3D Convolutional Networks on Multi-Core and Many-Core Shared Memory Machines

Aleksandar Zlateski, Kisuk Lee, H. Sebastian Seung

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Tags: CNN, Computer science, Computer vision, Deep learning, FFT, Intel Xeon Phi, Machine learning, Package

October 25, 2015 by hgpu

Multi-GPU Distributed Parallel Bayesian Differential Topic Modelling

Aaron Q Li

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Bayesian, Computer science, GPU cluster, Machine learning, NLP, nVidia, nVidia GeForce GTX 480, OpenCL, Thesis

October 25, 2015 by hgpu

Tuned and GPU-accelerated parallel data mining from comparable corpora

Krzysztof Wolk, Krzysztof Marasek

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Tags: Algorithms, Computer science, Data mining, Machine learning, NLP, nVidia, nVidia GeForce GTX 660

October 3, 2015 by hgpu

Fast Algorithms for Convolutional Neural Networks

Andrew Lavin

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Tags: Algorithms, CNN, Computer science, Deep learning, FFT, Image recognition, Machine learning, Neural networks

October 3, 2015 by hgpu

TABLA: A Unified Template-based Framework for Accelerating Statistical Machine Learning

Divya Mahajan, Jongse Park, Emmanuel Amaro, Hardik Sharma, Amir Yazdanbakhsh, Joon Kim, Hadi Esmaeilzadeh

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Tags: ARM, ASIC, Computer science, FPGA, Machine learning, nVidia, nVidia GeForce GTX 650 Ti, nVidia Jetson TK1, Performance, Tesla K40

September 29, 2015 by hgpu

From Pixels to Torques: Policy Learning using Deep Dynamical Convolutional Networks

John-Alexander M. Assael

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Tags: CNN, Computer science, CUDA, Deep learning, Lua, Machine learning, nVidia, Package, Tesla K40, Thesis

September 26, 2015 by hgpu

A Survey of CUDA-based Multidimensional Scaling on GPU Architecture

Hasmik Osipyan, Martin Krulis, Stephane Marchand-Maillet

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Tags: Algorithms, Computer science, CUDA, Machine learning, Multidimensional scaling, nVidia, nVidia GeForce GT 740 M, Pattern recognition

September 26, 2015 by hgpu

Autotuning Wavefront Patterns for Heterogeneous Architectures

Siddharth Mohanty

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, OpenCL, Performance, Thesis

September 19, 2015 by hgpu

linalg: Matrix Computations in Apache Spark

Reza Bosagh Zadeh, Xiangrui Meng, Burak Yavuz, Aaron Staple, Li Pu, Shivaram Venkataraman, Evan Sparks, Alexander Ulanov, Matei Zaharia

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Tags: Algorithms, Benchmarking, Computer science, CUBLAS, CUDA, Linear Algebra, Machine learning, Matrix multiplication, nVidia, Package, Scala, Tesla M2050

September 15, 2015 by hgpu

Refinements in Syntactic Parsing

David Hall

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Tags: Computer science, CUDA, Machine learning, NLP, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 690, Package, Scala, Thesis

September 15, 2015 by hgpu

Efficient Convolutional Neural Networks for Pixelwise Classification on Heterogeneous Hardware Systems

Fabian Tschopp

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Tags: AMD FirePro W9100, Artificial intelligence, ATI, Caffe, CNN, Computer science, Computer vision, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX 980, OpenCL, Package, Thesis

September 15, 2015 by hgpu

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

LC Framework

Characterizing the Performance of Parallel Data-Compression Algorithms across Compilers and GPUs

pplx-garden: Perplexity open source garden for inference technology

RDMA Point-to-Point Communication for LLM Systems

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high performance computing on graphics processing units: hgpu.org

Machine-Learning-based Performance Heuristics for Runtime CPU/GPU Selection

ZNN – A Fast and Scalable Algorithm for Training 3D Convolutional Networks on Multi-Core and Many-Core Shared Memory Machines

Multi-GPU Distributed Parallel Bayesian Differential Topic Modelling

Tuned and GPU-accelerated parallel data mining from comparable corpora

Fast Algorithms for Convolutional Neural Networks

TABLA: A Unified Template-based Framework for Accelerating Statistical Machine Learning

From Pixels to Torques: Policy Learning using Deep Dynamical Convolutional Networks

A Survey of CUDA-based Multidimensional Scaling on GPU Architecture

Autotuning Wavefront Patterns for Heterogeneous Architectures

linalg: Matrix Computations in Apache Spark

Refinements in Syntactic Parsing

Efficient Convolutional Neural Networks for Pixelwise Classification on Heterogeneous Hardware Systems

Recent source codes

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

LC Framework

pplx-garden: Perplexity open source garden for inference technology

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