high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

DeepFont: Identify Your Font from An Image

Zhangyang Wang, Jianchao Yang, Hailin Jin, Eli Shechtman, Aseem Agarwala, Jonathan Brandt, Thomas S. Huang

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Tags: CNN, Computer science, CUDA, Deep learning, Neural networks, nVidia

July 17, 2015 by hgpu

Overhauling SC atomics in C11 and OpenCL

John Wickerson

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Tags: Computer science, Heterogeneous systems, Memory model, OpenCL

July 17, 2015 by hgpu

Scaling Monte Carlo Tree Search on Intel Xeon Phi

S. Ali Mirsoleimani, Aske Plaat, Jaap van den Herik, Jos Vermaseren

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Tags: Algorithms, Artificial intelligence, Computer science, Intel Xeon Phi, Package

July 17, 2015 by hgpu

Automatic Optimization of Thread Mapping for a GPGPU Programming Framework

Kazuhiko Ohno, Tomoharu Kamiya, Takanori Maruyama, Masaki Matsumoto

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Tags: Benchmarking, Compilers, Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 980

July 15, 2015 by hgpu

Recovering Historical Climate Records using Artificial Neural Networks in GPU

Juan Pablo Balarini, Sergio Nesmachnow

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Tags: CUDA, Earth and Space Sciences, Image processing, Neural networks, nVidia, nVidia GeForce GTX 480

July 15, 2015 by hgpu

Performance analysis of GPGPU and CPU On AES Encryption

Akash Kiran Neelap

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Tags: AES, Algorithms, Computer science, CUDA, nVidia, nVidia Quadro K4000, Pthreads, Security, Thesis

July 15, 2015 by hgpu

Concurrent Manipulation of Dynamic Data Structures in OpenCL

Henk Mulder

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Tags: Algorithms, Computer science, Data Structures and Algorithms, nVidia, nVidia GeForce GT 310 M, OpenCL, Package

July 15, 2015 by hgpu

GPU-accelerated discontinuous Galerkin methods on hybrid meshes

Jesse Chan, Zheng Wang, Axel Modave, Jean-Francois Remacle, T. Warburton

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Tags: CUDA, Mathematics, Numerical Analysis, nVidia, nVidia GeForce GTX 980, OpenCL, OpenMP, Spectral elements, Wave equation

July 13, 2015 by hgpu

A Study of Data Partitioning on OpenCL-based FPGAs

Zeke Wang, Bingsheng He, Wei Zhang

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Tags: Computer science, Databases, FPGA, OpenCL

July 13, 2015 by hgpu

Optimization, Specification and Verification of the Prefix Sum Program in an OpenCL Environment

Thijs Wiefferink

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 770, OpenCL, Package

July 13, 2015 by hgpu

PLB-HeC: A Profile-based Load-Balancing algorithm for Heterogeneous CPU-GPU Clusters

Luis Sant'Ana, Raphael Camargo, Daniel Cordeiro

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Tags: Algorithms, Computer science, CUDA, GPU cluster, Heterogeneous systems, Linear Algebra, MPI, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, Tesla K20

July 13, 2015 by hgpu

Many-Core Compiler Fuzzing

Christopher Lidbury, Andrei Lascu, Nathan Chong, Alastair F. Donaldson

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Tags: ATI, ATI Radeon HD 6570, ATI Radeon HD 7970, Compilers, Computer science, FPGA, Intel HD 4600, Intel Xeon Phi, nVidia, nVidia GeForce GTX 770, nVidia GeForce GTX Titan, OpenCL, Tesla K40, Tesla M2050

July 10, 2015 by hgpu

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

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

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

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

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

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

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

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high performance computing on graphics processing units: hgpu.org

Programming

DeepFont: Identify Your Font from An Image

Overhauling SC atomics in C11 and OpenCL

Scaling Monte Carlo Tree Search on Intel Xeon Phi

Automatic Optimization of Thread Mapping for a GPGPU Programming Framework

Recovering Historical Climate Records using Artificial Neural Networks in GPU

Performance analysis of GPGPU and CPU On AES Encryption

Concurrent Manipulation of Dynamic Data Structures in OpenCL

GPU-accelerated discontinuous Galerkin methods on hybrid meshes

A Study of Data Partitioning on OpenCL-based FPGAs

Optimization, Specification and Verification of the Prefix Sum Program in an OpenCL Environment

PLB-HeC: A Profile-based Load-Balancing algorithm for Heterogeneous CPU-GPU Clusters

Many-Core Compiler Fuzzing

Recent source codes

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

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

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

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

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

True 4-Bit Quantized CNN Training on CPU

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

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