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MILJS: Brand New JavaScript Libraries for Matrix Calculation and Machine Learning

Ken Miura, Tetsuaki Mano, Atsushi Kanehira, Yuichiro Tsuchiya, Tatsuya Harada

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Tags: Computer science, Java, Machine learning, Mathematical Software, OpenCL, Package, Python

March 2, 2015 by hgpu

Accelerating Deep Convolutional Neural Networks Using Specialized Hardware

Kalin Ovtcharov, Olatunji Ruwase, Joo-Young Kim, Jeremy Fowers, Karin Strauss, Eric S. Chung

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Tags: Computer science, FPGA, Machine learning, Neural networks, Speech recognition

February 27, 2015 by hgpu

Face Detection on CUDA

Raksha Patel, Isha Vajani

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GT 410 M

February 27, 2015 by hgpu

A Graph-Partition-Based Scheduling Policy for Heterogeneous Architectures

Hao Wu, Daniel Lohmann, Wolfgang Schroder-Preikschat

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan, Task scheduling

February 27, 2015 by hgpu

Simulation of the hydrogen ground state in Stochastic Electrodynamics

Theo M. Nieuwenhuizen, Matthew T.P. Liska

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Tags: AMD Radeon R9 290X, ATI, ATI Radeon HD 6970, Electrodynamics, OpenCL, Physics, Quantum Physics

February 27, 2015 by hgpu

GPU accelerated image reconstruction in a two-strip J-PET tomograph

P. Bialas, J. Kowal, A. Strzelecki, T. Bednarski, E. Czerwinski, A. Gajos, D. Kaminska, L. Kaplon, A. Kochanowski, G. Korcyl, P. Kowalski, T. Kozik, W. Krzemien, E. Kubicz, P. Moskal, Sz. Niedzwiecki, M. Palka, L. Raczynski, Z. Rudy, O. Rundel, P. Salabura, N.G. Sharma, M. Silarski, A. Slomski, J. Smyrski, A. Wieczorek, W. Wislicki, M. Zielinski, N. Zon

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Tags: CUDA, Image reconstruction, Instrumentation and Detectors, Nuclear Experiment, nVidia, nVidia GeForce GTX 770, Physics

February 27, 2015 by hgpu

Implementation of Smith-Waterman algorithm in OpenCL for GPUs

Dzmitry Razmyslovich, Guillermo Marcus, Markus Gipp, Marc Zapatka, Andreas Szillus

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Tags: Bioinformatics, Biology, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Sequence alignment, Smith-Waterman algorithm

February 27, 2015 by azhar ali

Very Fast Non-Dominated Sorting

Czeslaw Smutnicki, Jaroslaw Rudy, Dominik Zelazny

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Tags: Algorithms, Computational Complexity, Computer science, CUDA, nVidia, Sorting, Tesla K20

February 24, 2015 by hgpu

Raster2Mesh: Rasterization based CVT meshing

Jonas Martinez, Frederic Claux, Sylvain Lefebvre

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX Titan, OpenGL, Rasterization, Tessellation, Voronoi diagram

February 24, 2015 by hgpu

A Vision for GPU-accelerated Parallel Computation on Geo-Spatial Datasets

Sushil K. Prasad, Michael McDermott, Satish Puri, Dhara Shah, Danial Aghajarian, Shashi Shekhar, Xun Zhou

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Tags: Computer science, CUDA, Databases, nVidia

February 24, 2015 by hgpu

A Virtual Machine Model for Accelerating Relational Database Joins using a General Purpose GPU

Kevin Angstadt, Ed Harcourt

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 760

February 24, 2015 by hgpu

Accelerating Lagrangian Particle Dispersion in the Atmosphere with OpenCL across Multiple Platforms

Paul Harvey, Saji Hameed, Wim Vanderbauwhede

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Tags: AMD Radeon R9 290X, ATI, CUDA, Earth and Space Sciences, Intel Xeon Phi, nVidia, nVidia GeForce GTX 580, OpenCL, Tesla C2075, Tesla K20, Weather prediction

February 24, 2015 by hgpu

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

Inside VOLT: Designing an Open-Source GPU Compiler (Tool)

SciDef: Automated Definition Extraction from Scientific Literature

SciDef: Automating Definition Extraction from Academic Literature with Large Language Models

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

BioAgent Bench: An AI Agent Evaluation Suite for Bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Private LLM Inference on Consumer Blackwell GPUs: A Practical Guide for Cost-Effective Local Deployment in SMEs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

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