Search Results for "benchmarks" - Page 12
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Showing 440 open source projects for "benchmarks"
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SSDB
A fast NoSQL database, an alternative to Redis
...Client API supports including C++, PHP, Python, Cpy, Java, nodejs, Ruby, Go(see all). Persistent queue service. Replication(master-slave), load balance. GUI administration tool(phpssdbadmin). Built-in CLI nagios self-checks. Benchmarks are taken by ssdb-bench(SSDB) and redis-benchmark(Redis). SSDB is licensed under New BSD License, a very flexible license to use. Drag the static libraies files into your iOS project. Then add ios/include to your iOS project's Header Search Paths, which is set in Build Settings. -
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SentEval
A python tool for evaluating the quality of sentence embeddings
SentEval is a standardized toolkit for evaluating sentence embeddings across a wide spectrum of downstream tasks and probing tests. It defines a simple interface—provide an encoder function from sentences to vectors—and then runs consistent training/evaluation loops for tasks like sentiment, entailment, paraphrase, and semantic textual similarity. The suite also contains linguistic probing tasks that illuminate what properties embeddings capture, such as tense, word order, or syntactic... -
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DeepCluster
Deep Clustering for Unsupervised Learning of Visual Features
...DeepCluster was one of the early successes in unsupervised visual feature learning, demonstrating that clustering-based reformulation can rival supervised baselines for many downstream tasks. The repository includes code for feature extraction, clustering, training loops, and evaluation benchmarks like linear probes. Because of its simplicity and modular design, DeepCluster has inspired many later methods. -
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Sparse Attention
"Generating Long Sequences with Sparse Transformers" examples
Sparse Attention is OpenAI’s code release for the Sparse Transformer model, introduced in the paper Generating Long Sequences with Sparse Transformers. It explores how modifying the self-attention mechanism with sparse patterns can reduce the quadratic scaling of standard transformers, making it possible to model much longer sequences efficiently. The repository provides implementations of sparse attention layers, training code, and evaluation scripts for benchmark datasets. It highlights... -
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PerfKit Benchmarker
PerfKit Benchmarker (PKB) contains a set of benchmarks
PerfKitBenchmarker is an open-source benchmarking framework designed to measure and compare the performance of cloud infrastructure across multiple providers in a consistent and reproducible way. It allows users to evaluate metrics such as latency, throughput, provisioning time, and system performance using a standardized set of benchmarks. The tool supports a wide range of environments, including major cloud platforms, Kubernetes clusters, and even local hardware, making it highly versatile for performance analysis. It simplifies the process of running complex benchmarks by providing unified command-line workflows that handle resource provisioning, execution, and result collection. ... -
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VideoPose3D
Efficient 3D human pose estimation in video using 2D keypoint
...By using only 2D detections (such as those from OpenPose or Detectron), it enables markerless 3D pose estimation with relatively lightweight computational requirements. The framework includes pretrained models, data preprocessing utilities, visualization tools, and evaluation scripts for standard benchmarks like Human3.6M. VideoPose3D has been used widely in computer vision research for human motion understanding, activity recognition, and animation generation. -
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Hiper
A statistical analysis tool for performance testing
...The tool repeatedly loads a specified webpage multiple times and gathers detailed timing metrics in order to produce more reliable performance measurements than single-run benchmarks. By averaging data across multiple page loads, Hiper helps developers understand whether performance optimizations actually improve real-world page loading behavior. The tool relies on browser performance timing data to capture metrics such as DNS lookup time, TCP connection time, time to first byte, download duration, DOM readiness, and total page load time. ... -
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COHCAP
City of Hope CpG Island Analysis Pipeline
...Please see the GitHub version: https://github.com/cwarden45/COHCAP This was the source repository for the Bioconductor version, with some changes after the decision to only provide the code through GitHub. 2) In addition to the original NAR paper, please see the following links: Benchmarks: http://www.nature.com/protocolexchange/protocols/2965#/introduction Protocol Exchange Files: http://sourceforge.net/projects/cohcap/files/Protocol_Exchange_Example.zip 3) Custom Annotation Files (including EPIC Array): https://sourceforge.net/projects/cohcap/files/additional_Bioconductor_annotations.zip/download -
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sysbench
Scriptable database and system performance benchmark
...New benchmarks can be easily created by implementing pre-defined hooks in user-provided Lua scripts. Can be used as a general-purpose Lua interpreter as well, simply replace #!/usr/bin/lua with #!/usr/bin/sysbench in your script. Execute events for this many seconds with statistics disabled before the actual benchmark run with statistics enabled. -
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RISC-V BOOM
SonicBOOM: The Berkeley Out-of-Order Machine
...The design is parameterizable, meaning users can tune pipeline widths, buffer sizes, functional units, and other microarchitectural knobs to explore tradeoffs. It is capable of booting Linux and running standard benchmarks, and its performance (measured in CoreMarks/MHz) is competitive with commercial cores. The project is intended primarily for hardware/architecture research and teaching, rather than production silicon, and typically is used in conjunction with SoC frameworks (for example via Chipyard) to integrate BOOM into larger systems. -
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decodIRT_BRACIS20
Decoding machine learning benchmarks
Archives of experiments performed and results obtained from the paper Decoding machine learning benchmarks -
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greenDAO
Light ORM solution for Android that maps objects to SQLite databases
Android ORM for your SQLite database. For new apps we recommend ObjectBox, a new object-oriented database that is much faster than SQLite and easier to use. For existing apps based on greenDAO we offer DaoCompat for an easy switch (see also the announcement). greenDAO is an open source Android ORM making development for SQLite databases fun again. It relieves developers from dealing with low-level database requirements while saving development time. SQLite is an awesome embedded relational... -
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jsprit
Open source toolkit for solving rich vehicle routing problems
jsprit is a java based, open-source toolkit for solving rich Traveling Salesman Problems(TSP) and Vehicle Routing Problems(VRP). It is lightweight, flexible and easy-to-use, and based on a single all-purpose meta-heuristic. Setting up the problem, defining additional constraints, modifying the algorithms and visualizing the discovered solutions is as easy and handy as reading classical VRP instances to benchmark your algorithm. It is fit for change and extension due to its modular design and... -
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VGGFace2
VGGFace2 Dataset for Face Recognition
...Alongside the dataset, the repository provides pre-trained models based on ResNet-50 and SE-ResNet-50 architectures, trained with both MS-Celeb-1M pretraining and fine-tuning on VGGFace2. These models achieve strong verification performance on benchmarks such as IJB-B and include variants with lower-dimensional embeddings for compact feature representation. The project also includes preprocessing tools, face detection scripts, and etc. -
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Bluebird
Full featured promise library with unmatched performance
...Bluebird still includes a lot of features like cancellation, iteration methods and warnings that native promises don't. If you are using Bluebird for performance rather than for those - please consider giving native promises a shot and running the benchmarks yourself. When using script tags the global variables Promise and P (alias for Promise) become available. Bluebird runs on a wide variety of browsers including older versions. Synchronous inspection allows you to retrieve the fulfillment value of an already fulfilled promise or the rejection reason of an already rejected promise synchronously. ... -
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Artemis-odb
A continuation of the popular Artemis ECS framework
...It is mature, actively maintained, and a continuation of the popular Artemis. Artemis-odb is one of the fastest incarnations of Artemis! Don't take our word for it, check out and run the benchmarks yourself! Dozens of games with sources are available in the Game Gallery! Use it commercially! Expand your toolkit! Easy migration from Artemis clones. Optionally auto-pooled components and hotspot optimization via compile-time bytecode instrumentation. High performance, GC-friendly, less boilerplate! Automatic tracking, and maintenance of entity relationships. -
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typesafe-actions
Typesafe utilities for "action-creators" in Redux / Flux Architecture
...The library supports integrations with common asynchronous approaches such as redux-observable and redux-saga. It is distributed in CommonJS, ES module, and UMD formats and includes runtime tests, type tests, and performance benchmarks intended to preserve type safety and efficiency. -
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Unused
A command line tool to identify unused code
Unused identifies unused code in Rails, Phoenix, and other types of applications, improving developer productivity. By default, unused leverages a different memory allocator called mimalloc. For my local benchmarks, it speeds up execution by a significant amount (which is documented in the commit introducing mimalloc), but currently runs into sporadic issues on Apple M1 devices. If you run into issues with segmentation faults, consider reinstalling unused with the stock Rust allocator. It is strongly recommended you install Universal Ctags to generate tags files. ... -
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libinstrument (ex libcsdbg)
C/C++ function instrumentation (AOP, exception/stack tracing, GC)
...The project comes with a CMake build system, integration with IDEs (CLion, Eclipse e.t.c) is straightforward. Using lazy algorithms there is virtually zero overhead in benchmarks and minimum overhead in execution time. Libinstrument tries to be as non-intrusive as possible, while trying to help the developer offering basic reflection. There are Unit Tests for each class and method, testing is driven with CTest. -
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InferSent
InferSent sentence embeddings
...Trained on large NLI datasets, the embeddings generalize across tasks like sentiment analysis, entailment, paraphrase detection, and semantic similarity with simple linear classifiers. The repository provides pretrained vectors, training scripts, and clear examples for evaluating transfer on a wide suite of benchmarks. Because the encoder is compact and language-agnostic at the interface level, it’s easy to drop into production pipelines that need robust semantic features. InferSent helped popularize the idea that supervised objectives (like NLI) can yield strong general-purpose sentence encoders, and it remains a reliable baseline against which to compare newer models. -
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dacapo-dl
Data and libraries supporting the DaCapo benchmarks
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benchm-ml
A benchmark of commonly used open source implementations
...It targets large scale settings by varying the number of observations (n) up to millions and the number of features (after expansion) to about a thousand, to stress test different implementations. The benchmarks cover algorithms like logistic regression, random forest, gradient boosting, and deep neural networks, and they compare across toolkits such as scikit-learn, R packages, xgboost, H2O, Spark MLlib, etc. The repository is structured in logical folders, each corresponding to algorithm categories. -
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GoJay
high performance JSON encoder/decoder with stream API for Golang
GoJay is a performant JSON encoder/decoder for Golang (currently the most performant, see benchmarks). It has a simple API and doesn't use reflection. It relies on small interfaces to decode/encode structures and slices. Gojay also comes with powerful stream decoding features and an even faster Unsafe API. There is also a code generation tool to make usage easier and faster. I looked at other fast decoders/encoders and realized it was mostly hardly readable static code generation or a lot of reflection had poor streaming features and were not so fast in the end. ... -
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ESRGAN
Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution
...It builds on earlier GAN-based approaches by improving network architecture (e.g., using Residual-in-Residual Dense Blocks), adversarial loss functions, and perceptual loss components to generate higher-fidelity high-resolution images from low-resolution inputs with more realistic textures and details. ESRGAN was originally developed as part of research efforts that won benchmarks such as the PIRM2018 super-resolution challenge, demonstrating that GAN-based techniques can produce visually convincing results that surpass traditional interpolation or earlier deep approaches. The repository provides the core testing and model definitions, allowing researchers and practitioners to reproduce results, experiment with pretrained models, and integrate ESRGAN into broader pipelines or applications. -
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HOBBIT Java SDK Example
Integrate your benchmarks and systems into the HOBBIT platform
Integrate your benchmarks and systems into the HOBBIT platform in 5 minutes. This repository contains all types of HOBBIT-compatible components and number of tests, required to debug components locally without having a running instance of the platform. The repository may be cloned and used as a HOBBIT-compatible basis for the future project (benchmark or system).
