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hgpu.org » Applications » Computer science

D-face: Parallel Implementation of CNN Based Face Classifier using Drone Data On K40 & Jetson TK1

Harish, Ayyappa, Santosh, P K Baruah, Kaliuday Balleda, Sairam K M Menon

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Tags: CNN, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, nVidia Jetson TK1, Tesla K40

March 8, 2016 by hgpu

Enhancing productivity and performance portability of OpenCL applications on heterogeneous systems using runtime optimizations

Thibaut Lutz

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Tags: Computer science, nVidia, nVidia GeForce GTX 780, OpenCL, Performance, performance portability, PTX, Thesis

March 8, 2016 by hgpu

Compiler and runtime techniques for bulk-synchronous programming models on CPU architectures

Hee-Seok Kim

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Tags: Compilers, Computer science, OpenCL, performance portability, Thesis

March 8, 2016 by hgpu

A Novel Mapping of Arbitrary Precision Integer Operations to the GPU

Matthias Gusenbauer

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Tags: Computer science, nVidia, nVidia GeForce GTX Titan X, OpenCL, Thesis

March 8, 2016 by hgpu

Performance Analysis of kNN on large datasets using CUDA & Pthreads

Sriram Kankatala

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Tags: Computer science, CUDA, Data mining, Databases, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX 550 Ti, Pattern recognition, Pthreads, Thesis

March 5, 2016 by hgpu

Input Space Splitting for OpenCL

Simon Moll, Johannes Doerfert, Sebastian Hack

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Tags: Compilers, Computer science, Intel, LLVM, OpenCL

March 5, 2016 by hgpu

Metamorphic Testing for (Graphics) Compilers

Alastair F. Donaldson, Andrei Lascu

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Tags: Compilers, Computer science, GLSL, nVidia, nVidia GeForce GTX 980 M, OpenCL, OpenGL

March 5, 2016 by hgpu

Hadoop Mapreduce OpenCL Plugin

Vivek Viswanathan

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Tags: AMD Radeon R9 290X, ATI, Computer science, Heterogeneous systems, Java, MapReduce, OpenCL

March 3, 2016 by hgpu

Hierarchical Semantic Parsing for Object Pose Estimation in Densely Cluttered Scenes

Chi Li, Jonathan Bohren, Eric Carlson, Gregory D. Hager

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Tags: Computer science, Computer vision, CUDA, nVidia, OpenCV, Package, SIFT

March 3, 2016 by hgpu

Heuristics for the Variable Sized Bin Packing Problem Using a Hybrid P-System and CUDA Architecture

Qadha'a AlEnezi, Hosam AboElFotoh, Bader AlBdaiwi, Mohammad Ali AlMulla

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 560 M, P systems

March 3, 2016 by hgpu

Proteus: Exploiting Numerical Precision Variability in Deep Neural Networks

P. Judd, J. Albericio, N. Enright Jerger, A. Moshovos, T. Hetherington, T. Aamodt

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Tags: Computer science, Deep learning, GPGPU-sim, Neural networks

March 3, 2016 by hgpu

DeepSpark: Spark-Based Deep Learning Supporting Asynchronous Updates and Caffe Compatibility

Hanjoo Kim, Jaehong Park, Jaehee Jang, Sungroh Yoon

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Tags: Caffe, Computer science, CUDA, Deep learning, Distributed computing, Java, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 970, Package

March 1, 2016 by hgpu

True 4-Bit Quantized CNN Training on CPU

True 4-Bit Quantized Convolutional Neural Network Training on CPU: Achieving Full-Precision Parity

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

Hunting CUDA Bugs at Scale with cuFuzz

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

MSKernelBench & CUDAMaster

Making LLMs Optimize Multi-Scenario CUDA Kernels Like Experts

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform

CONCUR: a benchmark designed to evaluate multithreaded Java code generated by LLMs

CONCUR: Benchmarking LLMs for Concurrent Code Generation

HIPRT: Ray Tracing using HIP

Ray Tracing using HIP

MXFP4 Training Support Codebase

Practical FP4 Training for Large-Scale MoE Models on Hopper GPUs

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high performance computing on graphics processing units: hgpu.org

Applications

D-face: Parallel Implementation of CNN Based Face Classifier using Drone Data On K40 & Jetson TK1

Enhancing productivity and performance portability of OpenCL applications on heterogeneous systems using runtime optimizations

Compiler and runtime techniques for bulk-synchronous programming models on CPU architectures

A Novel Mapping of Arbitrary Precision Integer Operations to the GPU

Performance Analysis of kNN on large datasets using CUDA & Pthreads

Input Space Splitting for OpenCL

Metamorphic Testing for (Graphics) Compilers

Hadoop Mapreduce OpenCL Plugin

Hierarchical Semantic Parsing for Object Pose Estimation in Densely Cluttered Scenes

Heuristics for the Variable Sized Bin Packing Problem Using a Hybrid P-System and CUDA Architecture

Proteus: Exploiting Numerical Precision Variability in Deep Neural Networks

DeepSpark: Spark-Based Deep Learning Supporting Asynchronous Updates and Caffe Compatibility

Recent source codes

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

MSKernelBench & CUDAMaster

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

CONCUR: a benchmark designed to evaluate multithreaded Java code generated by LLMs

HIPRT: Ray Tracing using HIP

MXFP4 Training Support Codebase

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