Search Results for "benchmark" - Page 3
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Showing 243 open source projects for "benchmark"
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LZ4
Extremely fast compression algorithm
...A high compression derivative, called LZ4_HC, is available, trading customizable CPU time for compression ratio. LZ4 library is provided as open-source software using a BSD license. This benchmark simulates simple "static content transfer" scenario such as OS Kernel compression or video game's static assets (text/images/tables/scripts/etc) which loading from Flash Memory / HDD / SSD. In this case, compression time is completely ignored. Because only content developers compress the data at once and usually they don't care about its computational cost. ... -
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TextDistance
Compute distance between sequences
...For main algorithms, text distance try to call known external libraries (fastest first) if available (installed in your system) and possible (this implementation can compare this type of sequences). Install text distance with extras for this feature. Textdistance use benchmark results for algorithm optimization and try to call the fastest external lib first (if possible). TextDistance show benchmarks results table for your system and saves libraries priorities into the libraries.json file in TextDistance's folder. This file will be used by text distance for calling the fastest algorithm implementation. ... -
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ARC-AGI
The Abstraction and Reasoning Corpus
ARC-AGI is a benchmark dataset and experimental framework designed to evaluate and advance artificial general intelligence by testing systems on abstract reasoning tasks that require human-like problem-solving abilities. It consists of a curated set of tasks where models must infer patterns from input-output examples and apply those rules to new unseen cases, without relying on memorization or prior training data. -
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PI-Based Image Encoder / Converter
Python code able to convert / compress image to PI (3.14, π) Indexes
...Features high-performance Numba-accelerated search and a signature 'film-grain' aesthetic upon reconstruction. ZIP also include 16 MB file with 16,7 mil numbers of PI Benchmark(Single-Thread): Hardware & Environment Apple Silicon: Apple M2 (Mac mini/MacBook) x86_64 Platform: Intel Core Ultra 5 225F (Arrow Lake, 10 Cores) OS 1: Fedora 43 (GNOME) OS 2: Windows 11 Pro (23H2/24H2) Software: Python 3.14.3 + Numba JIT (latest) Results (Lower is better) Platform / OS CPU Time (Seconds) macOS (Native) Apple M2 52.151311 s (in default setup) Fedora Linux Intel Core Ultra 5 225F 58.536457 s (in default Power Management: Balanced) Windows 11 Intel Core Ultra 5 225F 59.681427 s (important! ... -
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Hurt My CPU
Stress-Test your Processor
A simple tool which lets you spawn threads that do heavy work, thus hurting your CPU. -
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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... -
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The DaCapo Benchmark Suite
Benchmarking tool
This benchmark suite is intend as a tool for the research community. It consists of a set of open source, real world applications with non-trivial memory loads. -
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OpenDDS
OpenDDS is open source publish/subscribe middleware
OpenDDS is an open source implementation of the Object Management Group (OMG) Data Distribution Service (DDS), providing a publish/subscribe middleware solution for real-time distributed systems. OpenDDS includes development and run-time tools. Full product information, source code, documentation, build instructions, and license information are available from http://www.opendds.org. Commercial consulting, support, and training for OpenDDS are available. OpenDDS is in production use... -
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DIG
A library for graph deep learning research
...It includes unified implementations of data interfaces, common algorithms, and evaluation metrics for several advanced tasks. Our goal is to enable researchers to easily implement and benchmark algorithms. -
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FuzzBench
FuzzBench - Fuzzer benchmarking as a service
FuzzBench is a large-scale, open research platform developed by Google to evaluate and benchmark fuzzers — automated software testing tools that detect vulnerabilities through randomized input generation. It provides a standardized, reproducible environment for comparing the performance and effectiveness of different fuzzing algorithms on real-world software targets. FuzzBench integrates with the OSS-Fuzz infrastructure, allowing it to run experiments on authentic open source projects and collect meaningful data on crash discovery rates, code coverage, and bug-finding efficiency. ... -
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Pipeline
Banzai Cloud Pipeline is a solution-oriented application platform
Banzai Cloud Pipeline is a solution-oriented application platform which allows enterprises to develop, deploy and securely scale container-based applications in multi- and hybrid-cloud environments. Banzai Pipeline, or simply Pipeline is a tabletop reef break located in Hawaii, Oahu's North Shore. The most famous and infamous reef in the universe is the benchmark by which all other waves are measured. Banzai Cloud Pipeline is a solution-oriented application platform which allows enterprises to develop, deploy and securely scale container-based applications in multi- and hybrid-cloud environments. Provisioning: Provision highly available Kubernetes clusters on cloud providers, on-premise or hybrid configurations. ... -
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collectl
This is now also available here github.com/sharkcz/collectl.git
Collectl is a light-weight performance monitoring tool capable of reporting interactively as well as logging to disk. It reports statistics on cpu, disk, infiniband, lustre, memory, network, nfs, process, quadrics, slabs and more in easy to read format. -
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How They DevOps
A curated collection of publicly available resources
...This gives learners and teams a reality check: DevOps at scale is opinionated, messy, and adapted to business constraints. It’s especially useful for people building a DevOps function who want to benchmark against recognizable names before picking tools. The repository also serves as inspiration for internal presentations and proposals because you can say “this is how X does it” and back it up. Over time, as new companies publish engineering blogs and postmortems, the repo can be updated to reflect current industry setups. -
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AlphaTensor
AI discovers faster, efficient algorithms for matrix multiplication
...The repository is organized into four main components: algorithms, benchmarking, nonequivalence, and recombination. These contain implementations of the discovered matrix multiplication algorithms, tools to benchmark their real-world performance, proofs of nonequivalence among thousands of solutions, and methods for decomposing larger problems into smaller factorizations. Users can explore AlphaTensor’s discovered algorithms interactively using Colab notebooks or Python scripts. -
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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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Phoronix Test Suite
Open-Source, Automated Benchmarking
The Phoronix Test Suite is the most comprehensive testing and benchmarking platform available that provides an extensible framework for which new tests can be easily added. The Phoronix Test Suite is designed to effectively carry out both benchmarks in a clean, reproducible, and easy-to-use manner. -
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UVU
UVU is an extremely fast and lightweight test runner for Node.js
UVU is a lightweight, ultra-fast JavaScript test runner for Node.js and the browser created by Luke Edwards (lukeed). Its primary goal is to minimize overhead: startup time, memory usage, and complexity are all kept very low so that developers can write and run tests with minimal friction. The tool supports modern features like async/await and native ES Modules, making it suitable for modern codebases. It also supports running in browser environments, which makes it versatile for frontend... -
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CountBitsSet
minimal benchmark code for Counting Set Bits (ones) in an Integer
I was curious how much better the Algorithms, pointed out by BitTwiddling Hacks, perform than a simple Lookup Table approach... Now I think, perhaps my little investigation is interesting for others too... PS: the parallel counting Algo is about 35% faster on average on my computers than a simple LUT based solution. Also this shows nicely how different a human brain compatible solution is to a binary machine optimal solution :-) In the meantime I added other Algorithms beside... -
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Specter
Clojure(Script)'s missing piece
...Navigators can be composed with any other navigators, allowing sophisticated manipulations to be expressed very concisely. In addition, Specter has performance rivaling hand-optimized code (see this benchmark). Clojure's only comparable built-in operations are get-in and update-in, and the Specter equivalents are 30% and 85% faster, respectively (while being just as concise). Under the hood, Specter uses advanced dynamic techniques to strip away the overhead of composition. -
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Jour is designed to simplify the use of Javassist for processing multiple classes. In short Jour is simple Aspect Oriented Programming AOP framework on top of Javassist.
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Detectron2
Next-generation platform for object detection and segmentation
Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark. It is powered by the PyTorch deep learning framework. Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. Can be used as a library to support different projects on top of it. We'll open source more research projects in this way. It trains much faster. ... -
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DockStream
A Docking Wrapper to Enhance De Novo Molecular Design
DockStream is a docking wrapper providing access to a collection of ligand embedders and docking backends. Docking execution and post hoc analysis can be automated via the benchmarking and analysis workflow. The flexilibity to specifiy a large variety of docking configurations allows tailored protocols for diverse end applications. DockStream can also parallelize docking across CPU cores, increasing throughput. DockStream is integrated with the de novo design platform, REINVENT, allowing one... -
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CalDOM
An agnostic, reactive & minimalist (3kb) JavaScript UI library
...The overall performance drop is about 0.04x compared to vanilla/pure JavaScript. This is based on averaged unit-level benchmarks in handling single & multiple-element instances: View Benchmark Results against Vanilla JS, jQuery, React JS, Vue & more. -
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1m-go-tcp-server
Benchmarks for implementation of servers
1m-go-tcp-server is a benchmark collection for studying Go TCP server designs that can support one million connections. It compares different server architectures instead of presenting a single production framework. The repository includes implementations based on goroutines per connection, single epoll, multiple epoll loops, prefork design, worker pools, and Reactor-style event handling. -
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Awesome Graph Classification
Graph embedding, classification and representation learning papers
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers with reference implementations. Relevant graph classification benchmark datasets are available. Similar collections about community detection, classification/regression tree, fraud detection, Monte Carlo tree search, and gradient boosting papers with implementations.
