Projects with this topic
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Benchmarks data processing tools
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Cristian Vasu Data Portfolio / Database Performance Benchmarking with YCSB - Cassandra vs PostgreSQL
Benchmarked columnar vs row-oriented databases using the Yahoo Cloud Server Benchmark (YCSB). Compared throughput, latency, and error rates under different workloads. Analyzed trade-offs between NoSQL (Cassandra) and relational (PostgreSQL) databases with supporting graphs and configuration files.
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This C++ sample project uses meson to manage builds and already has auto-formatting, testing, linting, benchmarking, code coverage, static analysis and documentation generation.
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MultiNativQA is Multilingual Native question-answering (QA) dataset consisting of 64k QA pairs in seven extremely low to high resource languages, covering 18 different topics from nine different regions. Paper: https://arxiv.org/pdf/2407.09823. Project: https://nativqa.gitlab.io
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Benchmarking framework for machine learning with fNIRS
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QAPerf is a tool for evaluating the performance of quality assessment (QA) methods. It automates the generation of standard reports, including correlation tables, leave-one-group-out correlation boxplots, and other benchmarking visualizations. Designed for researchers and practitioners, QAPerf streamlines the analysis of QA metrics, ensuring reliable and reproducible evaluations.
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Command-line benchmarking tool. Runs commands, times them, ranks them. Also reports memory used, context switches, and other metrics.
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Server fibonacci benchmarks in three different technologies: node-js, vapor, php
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A Live Evaluation of Computational Methods for Metagenome Investigation
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A minimalistic and portable unit testing and benchmarking framework for C.
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Simple project to benchmark various sorting algorithms
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SecurityPerf is a tool designed for benchmarking production workloads. In doing so, it makes measuring the impact of security programs on production workloads easy.
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VTmark results, Ansible roles and other scripts.
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Pew Pew is a simple HTTPS benchmarking tool written in Go.
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The project uses natural language processing to automatically assess causal diagrams filled out by students based on semantic distance from the model causal diagram provided.
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Modular toolbox for performance recording, benchmarking and visualization. https://kpouget_spice.gitlab.io/streaming_stats/
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