Search Results for "benchmark"
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Showing 25 open source projects for "benchmark"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Stop Storing Third-Party Tokens in Your DatabaseRolling your own OAuth token storage can be a security liability. Token Vault securely stores access and refresh tokens from federated providers and handles exchange and renewal automatically. Connected accounts, refresh exchange, and privileged worker flows included.
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BenchmarkTools.jl
A benchmarking framework for the Julia language
...Under the hood, BenchmarkTrackers relied on Benchmarks for actual benchmark execution. -
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Crow Framework
A Fast and Easy to use microframework for the web
...Get started by installing Crow and building you first application. Or go through the guides if you're stuck somewhere. Easy Routing (similar to flask). Type-safe Handlers. Blazingly fast (see this benchmark and this benchmark). Built-in JSON support. Mustache-based templating library (crow::mustache). Header-only library (single header file available). Middleware support for extensions. HTTP/1.1 and Websocket support. Multi-part request and response support. Uses modern C++ (11/14). -
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golang-set
A simple generic set type for the Go language
...One common interface to both implementations, a nonthreadsafe implementation favoring performance, a threadsafe implementation favoring concurrent use. Feature complete set implementation modeled after Python's set implementation. Exhaustive unit-test and benchmark suite. This package is trusted by many companies and thousands of open-source packages. This package now fully supports generic syntax so you are now able to instantiate a collection for any comparable type object. -
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SIA
AI framework to autonomously improve the performance of any AI system
SIA is a self-improving AI framework designed to improve the performance of models or agents on benchmark tasks. It uses an iterative loop where a meta-agent creates or updates a task-specific target agent, while a feedback agent studies results and proposes improvements. The framework can refine both the harness around the task and the agent implementation itself. It is aimed at research and experimentation across tasks such as machine learning benchmarks, legal classification, code optimization, and scientific workflows. ... -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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Apache Sedona
Cluster computing framework for processing large-scale geospatial data
...Sedona extends existing cluster computing systems, such as Apache Spark and Apache Flink, with a set of out-of-the-box distributed Spatial Datasets and Spatial SQL that efficiently load, process, and analyze large-scale spatial data across machines. According to our benchmark and third-party research papers, Sedona runs 2X - 10X faster than other Spark-based geospatial data systems on computation-intensive query workloads. According to our benchmark and third-party research papers, Sedona has 50% less peak memory consumption than other Spark-based geospatial data systems for large-scale in-memory query processing. ... -
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Python Outlier Detection
A Python toolbox for scalable outlier detection
...PyOD contains multiple models that also exist in scikit-learn. It is possible to train and predict with a large number of detection models in PyOD by leveraging SUOD framework. A benchmark is supplied for select algorithms to provide an overview of the implemented models. In total, 17 benchmark datasets are used for comparison, which can be downloaded at ODDS. -
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Django Cachalot
No effort, no worry, maximum performance
...You will need a database called "cachalot" on MySQL and PostgreSQL. Additionally, on PostgreSQL, you will need to create a role called "cachalot." You can also run the benchmark, and it'll raise errors with specific instructions for how to fix it. Use cachalot for cold or modified <50 times per minutes (Most people should stick with only cachalot since you most likely won't need to scale to the point of needing cache-machine added to the bowl). -
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Fiber
Express inspired web framework written in Go
...You can also serve the contents of multiple directories on the same route! Since Fiber is built on top of Fasthttp, your apps will enjoy unmatching performance! Don't believe us? Here's a benchmark that proves how Fiber shines compared to other frameworks. Are you building an API server? We've got you covered! Fiber is the perfect choice for building REST APIs in Go. Receiving and sending data is fast and easy! -
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MMDeploy
OpenMMLab Model Deployment Framework
MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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hashmap
A Golang lock-free thread-safe HashMap optimized for fastest access
...Reading from the hash map for numeric key types in a thread-safe way is faster than reading from a standard Golang map in an unsafe way and four times faster than Golang's sync.Map. Technical design decisions have been made based on benchmarks that are stored in an external repository: go-benchmark. The library uses a sorted linked list and a slice as an index into that list. The Get() function contains helper functions that have been inlined manually until the Golang compiler will inline them automatically. It optimizes the slice access by circumventing the Golang size check when reading from the slice. -
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Yandex Tank
Load and performance benchmark tool
Yandex.Tank is an extensible open-source load testing tool for advanced Linux users which is especially good as a part of an automated load testing suite. Different load generators are supported. Evgeniy Mamchits' phantom is a very fast (100 000+ RPS) shooter written in C++ (default) JMeter is an extendable and widely known one. BFG is a Python-based generator that allows you to write your load scenarios in Python. Experimental Golang generator: pandora. Performance analytics backend... -
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Dopamine
Framework for prototyping of reinforcement learning algorithms
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms. It aims to fill the need for a small, easily grokked codebase in which users can freely experiment with wild ideas (speculative research). This first version focuses on supporting the state-of-the-art, single-GPU Rainbow agent (Hessel et al., 2018) applied to Atari 2600 game-playing (Bellemare et al., 2013). Specifically, our Rainbow agent implements the three components identified as most important... -
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RefineNet
RefineNet: Multi-Path Refinement Networks
...It implements the architecture presented in the CVPR 2017 paper RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation and its extended version published in TPAMI 2019. The framework uses multi-path refinement and improved residual pooling to achieve high-quality segmentation results across multiple benchmark datasets. It provides trained models for datasets such as PASCAL VOC 2012, Cityscapes, NYUDv2, Person_Parts, PASCAL_Context, SUNRGBD, and ADE20k, with versions based on ResNet-101 and ResNet-152 backbones. The repository supports both single-scale and multi-scale prediction, with scripts for training, testing, and evaluating segmentation performance. ... -
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Oyente
An Analysis Tool for Smart Contracts
...To run the benchmarks, it is best to use the docker container as it includes the blockchain snapshot necessary. In the container, run batch_run.py after activating the virtualenv. Results are in results.json once the benchmark completes. -
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Crow
Crow is very fast and easy to use C++ micro web framework
Crow is C++ microframework for web. (inspired by Python Flask). If you just want to use crow, copy amalgamate/crow_all.h and include it. C++ compiler with good C++11 support (tested with g++>=4.8). Provide an amalgamated header file crow_all.h with every features. Handler arguments type check at compile time. Now supporting VS2013 with limited functionality (only run-time check for url is available.) Out-of-source build with CMake is recommended. -
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TRMSim-WSN (Trust and Reputation Models Simulator for Wireless Sensor Networks) is a Java-based simulator aimed to test Trust and Reputation models for WSNs. It provides several Trust and Reputation models and new ones can be easily added.
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MongoLantern - MongoDB Fulltext Search
Open Source MongoDB Fulltext Search Server
MongoLantern is an open source full text search server using MongoDB as index storage, which allows MongoLantern to migrate any changes very easily into account using MongoDB API. It's written originally written in PHP can be migrated to any desired language as required using it's future APIs. MongoLantern 0.7 - Stable/Production Release: 1. MongoLantern API support enabled. 2. CSV indexer added as a plugin. 3. node.js API client added. -
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A fully automated database benchmark suite that prints tabular and graphic results for multiple tested disciplines, given JDBC database connections. Some free open source database engines are included.
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IMPORTANT: This project is no longer maintained. All the effort is targeted on project Radargun: http://radargun.sourceforge.net
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Set of applet, test framework and JUnit test applications to measure the efficiency of modular operations and exponentiations on java cards.
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An open source framework for unit test and performance benchmark, initiated by Andrew Zhang. p-unit supports to run the same tests with single thread or multi-threads, tracks memory and time consumption, and generates the result as pdf/jpg/png/txt file.
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AdaptiveCells J2EE generates test-beds for benchmarking J2EE performance. They consists of highly customizable EJB cells that can emulate CPU load, memory usage, memory leaks and exceptions. The behaviour of the cells is coordinated from a web front-end.
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Project aims to simplify Linux kernel analysis and development. Primary audience to the result of project will be (under)graduate students attending "Operating system" courses. It is our intention to make advances with every generation of students.
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A generic java based distributed performance testing platform specifically for testing clustered or distributed applications and or frameworks. The framework itself is clustered and coordinated with www.terracotta.org
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