Machine learning | Page 47

hgpu.org » Machine learning

Large-Scale Deep Learning on the YFCC100M Dataset

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

View

Download (PDF)

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

February 13, 2015 by hgpu

Sparse Matrix-Vector Multiplication on GPU

Arash Ashari

View

Download (PDF)

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

Scaling Recurrent Neural Network Language Models

Will Williams, Niranjani Prasad, David Mrva, Tom Ash, Tony Robinson

View

Download (PDF)

Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan

February 3, 2015 by hgpu

On Vectorization of Deep Convolutional Neural Networks for Vision Tasks

Jimmy SJ. Ren, Li Xu

View

Download (PDF)

Source codes

Tags: CNN, Computer science, Computer vision, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 780 Ti, Package

January 30, 2015 by hgpu

maxDNN: An Efficient Convolution Kernel for Deep Learning with Maxwell GPUs

Andrew Lavin

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Machine learning, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 980, Package

January 28, 2015 by hgpu

Revisit Long Short-Term Memory: An Optimization Perspective

Qi Lyu, Jun Zhu

View

Download (PDF)

Tags: Computer science, CUDA, Machine learning, MapReduce, Neural networks, nVidia, nVidia GeForce GTX 770

January 23, 2015 by hgpu

Accelerating mahout on heterogeneous clusters using HadoopCL

Xiangyu Li

View

Download (PDF)

Tags: Cluster computing, Computer science, GPU cluster, Heterogeneous systems, Java, Machine learning, MapReduce, nVidia, OpenCL, Tesla K20, Thesis

January 19, 2015 by hgpu

Image Super-Resolution Using Deep Convolutional Networks

Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang

View

Download (PDF)

Source codes

Tags: CNN, Computer science, CUDA, Machine learning, Neural networks, nVidia, Package

January 10, 2015 by hgpu

Cardiac Dysrhythmia Detection with GPU-Accelerated Neural Networks

Albert Haque

View

Download (PDF)

Source codes

Tags: CUDA, Machine learning, Medicine, Neural networks, nVidia, nVidia GeForce GTX 750 Ti, Package

January 8, 2015 by hgpu

Disjunctive Normal Networks

Mehdi Sajjadi, Mojtaba Seyedhosseini, Tolga Tasdizen

View

Download (PDF)

Tags: Computer science, Computer vision, CUDA, Machine learning, Neural and Evolutionary Computing, Neural networks, nVidia

January 2, 2015 by hgpu

Spectral classification using convolutional neural networks

Pavel Hala

View

Download (PDF)

Tags: Astrophysics, Computer science, CUDA, Instrumentation and Methods for Astrophysics, Machine learning, Neural and Evolutionary Computing, nVidia, Thesis

December 30, 2014 by hgpu

Automatic Tuning of Local Memory Use on GPGPUs

Tianyi David Han, Tarek S. Abdelrahman

View

Download (PDF)

Tags: Benchmarking, Computer science, Machine learning, nVidia, OpenCL, Performance, Tesla M2090

December 26, 2014 by hgpu

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Specx: Speculative task-based runtime system

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Large-Scale Deep Learning on the YFCC100M Dataset

Sparse Matrix-Vector Multiplication on GPU

Scaling Recurrent Neural Network Language Models

On Vectorization of Deep Convolutional Neural Networks for Vision Tasks

maxDNN: An Efficient Convolution Kernel for Deep Learning with Maxwell GPUs

Revisit Long Short-Term Memory: An Optimization Perspective

Accelerating mahout on heterogeneous clusters using HadoopCL

Image Super-Resolution Using Deep Convolutional Networks

Cardiac Dysrhythmia Detection with GPU-Accelerated Neural Networks

Disjunctive Normal Networks

Spectral classification using convolutional neural networks

Automatic Tuning of Local Memory Use on GPGPUs

Recent source codes

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

Specx: Speculative task-based runtime system

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

Most viewed papers (last 30 days)