high performance computing on graphics processing units: hgpu.org

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Communication Optimization for Multi GPU Implementation of Smith-Waterman Algorithm

Sampath Kumar, P. K. Baruah

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Tags: Algorithms, Biology, Computational biology, CUDA, Databases, nVidia, Sequence matching, Smith-Waterman algorithm, Tesla M2050

November 2, 2013 by hgpu

A Datalog Engine for GPUs

Carlos Alberto Martinez-Angeles, Ines Dutra, Vitor Santos Costa, Jorge Buenabad-Chavez

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 580

October 25, 2013 by hgpu

Solving Multiple Queries through a Permutation Index in GPU

Mariela Lopresti, Natalia Miranda, Fabiana Piccoli, Nora Reyes

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce GT 520 M, nVidia GeForce GTX 330 M, nVidia GeForce GTX 550 Ti, Search

October 21, 2013 by hgpu

VDBSCAN+: Performance Optimization Based on GPU Parallelism

Carlos Roberto Valencio, Guilherme Priolli Daniel, Camila Alves de Medeiros, Adriano Mauro Cansian

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Tags: Algorithms, Computer science, CUDA, Data mining, Databases, nVidia, nVidia GeForce GT 525 M

October 18, 2013 by hgpu

Hardware-Oblivious Parallelism for In-Memory Column-Stores

Max Heimel, Michael Saecker, Holger Pirk, Stefan Manegold, Volker Markl

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Tags: Computer science, Databases, nVidia, nVidia GeForce GTX 460, OpenCL

September 11, 2013 by hgpu

Skew Handling in Aggregate Streaming Queries on GPUs

G. Koutsoumpakis, I. Koutsoumpakis, A. Gounaris

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Tags: CUDA, Databases, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 550 Ti, Performance

September 6, 2013 by hgpu

Why it is time for a HyPE: A Hybrid Query Processing Engine for Efficient GPU Coprocessing in DBMS

Sebastian Bress

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Tags: Algorithms, Computer science, Databases, Heterogeneous systems

August 21, 2013 by hgpu

Permutation Index and GPU to Solve efficiently Many Queries

Mariela Lopresti, Natalia Miranda, Fabiana Piccoli, Nora Reyes

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GT 520 M, nVidia GeForce GTX 330 M, nVidia GeForce GTX 550 Ti

August 18, 2013 by hgpu

The Yin and Yang of Processing Data Warehousing Queries on GPU Devices

Yuan Yuan, Rubao Lee, Xiaodong Zhang

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Tags: Analytical model, ATI, ATI Radeon HD 7970, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Package

August 14, 2013 by hgpu

Sequence Data Indexing Method Exploiting the Parallel Processing Resources of GPGPU

Taehwan Kim, Seokil Song, Dojin Choi, Yunsik Kwak, Bongen Goo

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 670

August 10, 2013 by hgpu

GPU Parallel Algorithms for Reporting Movement Behaviour Patterns in Spatiotemporal Databases

Nacho Valladares Cereceda

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Tags: Algorithms, Computer science, CUDA, Data mining, Databases, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Thesis

July 27, 2013 by hgpu

Multi-core CUDA Architecture for Parallelization of Hierarchical Text Clustering

Debasis Pattanaik, Ajaya Kumar Malik, Pradeep Kumar Mallick

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Tags: Clustering, Computer science, CUDA, Databases, Hierarchical clustering, nVidia, nVidia GeForce 8800 GTX

July 22, 2013 by hgpu

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

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

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

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

Generating Literature-Driven Scientific Theories at Scale

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high performance computing on graphics processing units: hgpu.org

Communication Optimization for Multi GPU Implementation of Smith-Waterman Algorithm

A Datalog Engine for GPUs

Solving Multiple Queries through a Permutation Index in GPU

VDBSCAN+: Performance Optimization Based on GPU Parallelism

Hardware-Oblivious Parallelism for In-Memory Column-Stores

Skew Handling in Aggregate Streaming Queries on GPUs

Why it is time for a HyPE: A Hybrid Query Processing Engine for Efficient GPU Coprocessing in DBMS

Permutation Index and GPU to Solve efficiently Many Queries

The Yin and Yang of Processing Data Warehousing Queries on GPU Devices

Sequence Data Indexing Method Exploiting the Parallel Processing Resources of GPGPU

GPU Parallel Algorithms for Reporting Movement Behaviour Patterns in Spatiotemporal Databases

Multi-core CUDA Architecture for Parallelization of Hierarchical Text Clustering

Recent source codes

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

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

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

Vortex-Optimized Light-weight Toolchain (VOLT)

SciDef: Automated Definition Extraction from Scientific Literature

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

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

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