Search Results for "benchmark"
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Showing 748 open source projects for "benchmark"
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Benchmark
A microbenchmark support library
A library to benchmark code snippets, similar to unit tests. -
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LZ4
Extremely fast compression algorithm
LZ4 is lossless compression algorithm, providing compression speed > 500 MB/s per core (>0.15 Bytes/cycle). It features an extremely fast decoder, with speed in multiple GB/s per core (~1 Byte/cycle). 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... -
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XMRig
RandomX, KawPow, CryptoNight, AstroBWT and GhostRider unified miner
High performance, open-source, cross-platform RandomX, KawPow, CryptoNight, and AstroBWT CPU/GPU miner, RandomX benchmark, and stratum proxy. XMRig is a high-performance, open-source, cross-platform RandomX, KawPow, CryptoNight, and AstroBWT unified CPU/GPU miner and RandomX benchmark. Official binaries are available for Windows, Linux, macOS, and FreeBSD. The preferred way to configure the miner is the JSON config file as it is more flexible and human-friendly. The command-line interface does... -
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KonaBess
A GPU overclock & undervolt tool for various Snapdragon chips
KonaBess is a straightforward application designed to customize GPU frequency and voltage tables without the need for kernel recompilation. The application achieves customization by unpacking the Boot/Vendor Boot image, decompiling and editing relevant dtb (device tree binary) files, and finally repacking and flashing the modified image. The extent of improvement varies, with some users reporting a 25% reduction in power consumption in the graphics benchmark (4.2w->3.2w) after undervolting... -
Picsart Enterprise Background Removal API for Stunning eCommerce VisualsWith our Remove Background API tool, you can access the transformative capabilities of automation , which will allow you to turn any photo asset into compelling product imagery. With elevated visuals quality on your digital platforms, you can captivate your audience, and therefore achieve higher engagement and sales.
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rathole
A lightweight and high-performance reverse proxy for NAT traversal
A secure, stable and high-performance reverse proxy for NAT traversal, written in Rust. rathole, like frp and ngrok, can help to expose the service on the device behind the NAT to the Internet, via a server with a public IP. High Performance Much higher throughput can be achieved than frp, and more stable when handling a large volume of connections. Low Resource Consumption Consumes much fewer memory than similar tools. See Benchmark. The binary can be as small as ~500KiB to fit the constraints... -
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K9s
Kubernetes CLI To Manage Your Clusters In Style!
... support to extend K9s to create your very own cluster commands. Powerful filtering mode to allow user to drill down and view workload related resources. Supports for viewing RBAC rules such as cluster/roles and their associated bindings. Reverse lookup to asserts what a user/group or ServiceAccount can do on your clusters. You can benchmark your HTTP services/pods directly from K9s to see how your application fare and adjust your resources request/limit accordingly. -
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Crow Framework
A Fast and Easy to use microframework for the web
... 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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BEIR
A Heterogeneous Benchmark for Information Retrieval
BEIR is a benchmark framework for evaluating information retrieval models across various datasets and tasks, including document ranking and question answering. -
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kube-bench
Checks whether Kubernetes is deployed
kube-bench is a tool that checks whether Kubernetes is deployed securely by running the checks documented in the CIS Kubernetes Benchmark. Trivy, the all-in-one cloud-native security scanner, can be deployed as a Kubernetes Operator inside a cluster. Both, the Trivy CLI, and the Trivy Operator support CIS Kubernetes Benchmark scanning among several other features. There are multiple ways to run kube-bench. You can run kube-bench inside a pod, but it will need access to the host's PID namespace... -
Powering the best of the internet | FastlyEnsure your websites, applications and services can effortlessly handle the demands of your users with Fastly. Fastly’s portfolio is designed to be highly performant, personalized and secure while seamlessly scaling to support your growth.
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GoNB
GoNB, a Go Notebook Kernel for Jupyter
Go is a compiled language, but with very fast compilation, that allows one to use it in a REPL (Read-Eval-Print-Loop) fashion, by inserting a "Compile" step in the middle of the loop -- so it's a Read-Compile-Run-Print-Loop — while still feeling very interactive. GoNB leverages that compilation speed to implement a full-featured (at least it's getting there) Jupyter notebook kernel. As a side benefit it works with packages that use CGO — although it won't parse C code in the cells, so it... -
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Apache Sedona
Cluster computing framework for processing large-scale geospatial data
Apache Sedona™ is a cluster computing system for processing large-scale spatial 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... -
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pnpm
Fast, disk space efficient package manager
Fast, disk space efficient package manager. pnpm uses a content-addressable filesystem to store all files from all module directories on a disk. When using npm, if you have 100 projects using lodash, you will have 100 copies of lodash on disk. With pnpm, lodash will be stored in a content-addressable storage. Files inside node_modules are cloned or hard-linked from a single content-addressable storage. pnpm has built-in support for multiple packages in a repository. pnpm creates a non-flat... -
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OrdinaryDiffEq.jl
High performance ordinary differential equation (ODE)
This is a suite for numerically solving differential equations written in Julia and available for use in Julia, Python, and R. The purpose of this package is to supply efficient Julia implementations of solvers for various differential equations. The well-optimized DifferentialEquations solvers benchmark as some of the fastest implementations, using classic algorithms and ones from recent research that routinely outperform the “standard” C/Fortran methods, and include algorithms optimized... -
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Prowler
An open source security tool to perform AWS security assessment
... Foundations Benchmark (49 checks) and has more than 100 additional checks related to GDPR, HIPAA, PCI-DSS, ISO-27001, FFIEC, SOC2, and others. +200 checks covering security best practices across all AWS regions and most AWS services. Get a direct colorful or monochrome report. Get an HTML, CSV, JUNIT, JSON, or JSON ASFF (Security Hub) format report. -
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Nightingale
A distributed and high-performance monitoring system
Nightingale is a distributed and high-performance monitoring system. Prometheus enterprise edition. Nightingale is a new generation of domestic intelligent monitoring system. It has good support for cloud-native scenarios and traditional physical machine virtual machine scenarios. It takes 10 minutes to complete the construction and is familiar with use in 1 hour. It has been verified by the massive data of the production environment of Didi, and hopes to create a benchmark for domestic... -
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Smile
Statistical machine intelligence and learning engine
Smile is a fast and comprehensive machine learning engine. With advanced data structures and algorithms, Smile delivers the state-of-art performance. Compared to this third-party benchmark, Smile outperforms R, Python, Spark, H2O, xgboost significantly. Smile is a couple of times faster than the closest competitor. The memory usage is also very efficient. If we can train advanced machine learning models on a PC, why buy a cluster? Write applications quickly in Java, Scala, or any JVM languages... -
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Trivy Operator
Kubernetes-native security toolkit
The Trivy Operator leverages Trivy to continuously scan your Kubernetes cluster for security issues. The scans are summarised in security reports as Kubernetes Custom Resource Definitions, which become accessible through the Kubernetes API. The Operator does this by watching Kubernetes for state changes and automatically triggering security scans in response. For example, a vulnerability scan is initiated when a new Pod is created. This way, users can find and view the risks that relate to... -
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Rbatis
Rust High Performance compile-time ORM(RBSON based)
A highly Performant, Safe, Dynamic SQL(Compile-time) ORM framework written in Rust, inspired by Mybatis and MybatisPlus. Zero cost Dynamic SQL, implemented using (proc-macro,compile-time, Cow (Reduce unnecessary cloning)) techniques, don't need ONGL engine(mybatis) Free deserialization, Auto Deserialize to any struct(Option,Map,Vec...) High performance, Based on Future, with async_std/tokio, single threaded benchmark can easily achieve 200,000 QPS. logical deletes, pagination, py-like SQL... -
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MLPerf
Reference implementations of MLPerf™ training benchmarks
This is a repository of reference implementations for the MLPerf training benchmarks. These implementations are valid as starting points for benchmark implementations but are not fully optimized and are not intended to be used for "real" performance measurements of software frameworks or hardware. Benchmarking the performance of training ML models on a wide variety of use cases, software, and hardware drives AI performance across the tech industry. The MLPerf Training working group draws... -
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Python Outlier Detection
A Python toolbox for scalable outlier detection
... network-based models, e.g., AutoEncoders, which are implemented in both PyTorch and Tensorflow. 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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PlatEMO
Evolutionary multi-objective optimization platform
Evolutionary multi-objective optimization platform. PlatEMO consists of a number of MATLAB functions without using any other libraries. Any machines able to run MATLAB can use PlatEMO regardless of the operating system. PlatEMO includes more than ninety existing popular MOEAs, including genetic algorithm, differential evolution, particle swarm optimization, memetic algorithm, estimation of distribution algorithm, and surrogate model-based algorithm. Most of them are representative algorithms... -
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Snappy
A fast compressor/decompressor
... 250 MB/sec or more and decompresses at about 500 MB/sec or more. (These numbers are for the slowest inputs in our benchmark suite; others are much faster.) In our tests, Snappy usually is faster than algorithms in the same class (e.g. LZO, LZF, QuickLZ, etc.) while achieving comparable compression ratios. -
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Tile38
Ultra Fast Geospatial Database & Geofencing Server
... components: the server, command line interface tool and server benchmark tool. It is completely free and open source and is available for OSX, Linux, FreeBSD, and Windows. -
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hyperfine
A command-line benchmarking tool
A command-line benchmarking tool. Statistical analysis across multiple runs. Support for arbitrary shell commands. Constant feedback about the benchmark progress and current estimates. Warmup runs can be executed before the actual benchmark. Cache-clearing commands can be set up before each timing run. Statistical outlier detection to detect interference from other programs and caching effects. Export results to various formats: CSV, JSON, Markdown, AsciiDoc. Parameterized benchmarks (e.g. vary... -
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Terrascan
Detect compliance and security violations across Infrastructure
Detect compliance and security violations across Infrastructure as Code to mitigate risk before provisioning cloud native infrastructure. As you embrace Infrastructure as Code (IaC) such as Terraform, Kubernetes, Argo CD, Atlantis and AWS CloudFormation, it is important to ensure that security best practices and compliance requirements are observed. Terracan provides 500+ out-of-the-box policies so that you can scan IaC against common policy standards such as the CIS Benchmark. It leverages...
