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Study and evaluation of an Irregular Graph Algorithm on Multicore and GPU Processor Architectures

Varun Nagpal

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Performance, Tesla C1060, Thesis

March 10, 2016 by hgpu

Testing fine-grained parallelism for the ADMM on a factor-graph

Ning Hao, AmirReza Oghbaee, Mohammad Rostami, Nate Derbinsky, Jose Bento

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Tags: Algorithms, Computer science, CUDA, Mathematical Software, nVidia, OpenMP, Package, Tesla K40

March 10, 2016 by hgpu

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

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

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

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

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

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high performance computing on graphics processing units: hgpu.org

Applications

Study and evaluation of an Irregular Graph Algorithm on Multicore and GPU Processor Architectures

Testing fine-grained parallelism for the ADMM on a factor-graph

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

Hierarchical Semantic Parsing for Object Pose Estimation in Densely Cluttered Scenes

Hadoop Mapreduce OpenCL Plugin

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

Recent source codes

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

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

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