Search Results for "performance kpi management" - Page 5

Showing 860 open source projects for "performance kpi management"

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    Red Hat Enterprise Linux on Microsoft Azure

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  • 1
    Rook

    Rook

    Storage Orchestration for Kubernetes

    Rook turns distributed storage systems into self-managing, self-scaling, self-healing storage services. It automates the tasks of a storage administrator: deployment, bootstrapping, configuration, provisioning, scaling, upgrading, migration, disaster recovery, monitoring, and resource management. Rook orchestrates the Ceph storage solution, with a specialized Kubernetes Operator to automate management. Rook ensures that Ceph will run well on Kubernetes and simplify the deployment and management...
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  • 2
    YAO

    YAO

    Yao A low code engine to create web services and dashboard

    ... efficient than traditional programming languages ​​in terms of reusability and coding efficiency; application performance and resource ratio Better than PHP, JAVA and other languages. Yao has a built-in data management system. By writing JSON to describe the interface layout, 90% of the common interface interaction functions can be realized. It is especially suitable for quickly making various management backgrounds, CRM, ERP, and other internal enterprise systems.
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  • 3
    Nuke

    Nuke

    Image loading system

    ... and optimized for performance. Fast LRU memory cache, native HTTP disk cache, and custom aggressive LRU disk cache. Customize image pipeline using built-in Alamofire, Gifu, FLAnimatedImage, WebP plugins or create your own. Enable progressive decoding with a single line of code. Nuke supports progressive JPEG out of the box, and WebP via a plugin built by the community. Automatically prefetch images ahead of time using either Preheat or native table and collection view prefetching APIs.
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  • 4
    KOOM

    KOOM

    KOOM is an OOM killer on mobile platform by Kwai

    ... management of the Kuaishou client. In the daily version iteration process, OOM surges occasionally occur, and the online environment is very complicated. There are thousands of AB experiments. Pre-prevention and post-recovery cannot be achieved. Therefore, high-performance online memory monitoring solutions are urgently needed.
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  • 5
    TDengine

    TDengine

    Open-source time-series database with high-performance and scalability

    Enables efficient, real-time data ingestion, processing and monitoring of TB and even PB scale data per day, generated by billions of sensors and data collectors. TDengine can be widely applied to IoT, Industrial Internet, Connected Vehicles, DevOps, Energy , Finance and many other use-cases. TDengine’s innovative design and purpose-built storage engine outperforms other time-series databases for data ingestion, querying and data compression while significantly reducing storage and computing...
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  • 6
    ClusterFuzz

    ClusterFuzz

    Scalable fuzzing infrastructure

    ... multiple coverage guided fuzzing engines (libFuzzer, AFL, AFL++ and Honggfuzz) for optimal results (with ensemble fuzzing and fuzzing strategies). Statistics for analyzing fuzzer performance, and crash rates. Easy to use web interface for management and viewing crashes. Support for various authentication providers using Firebase.
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  • 7
    ReactiveMP.jl

    ReactiveMP.jl

    High-performance reactive message-passing based Bayesian engine

    ReactiveMP.jl is a Julia package that provides an efficient reactive message passing based Bayesian inference engine on a factor graph. The package is a part of the bigger and user-friendly ecosystem for automatic Bayesian inference called RxInfer. While ReactiveMP.jl exports only the inference engine, RxInfer provides convenient tools for model and inference constraints specification as well as routines for running efficient inference both for static and real-time datasets.
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  • 8
    AppleAccelerate.jl

    AppleAccelerate.jl

    Julia interface to the macOS Accelerate framework

    Julia interface to the macOS Accelerate framework. This provides a Julia interface to some of the macOS Accelerate frameworks. At the moment, this package provides access to Accelerate BLAS and LAPACK using the libblastrampoline framework, an interface to the array-oriented functions, which provide a vectorized form for many common mathematical functions. The performance is significantly better than using standard libm functions in some cases, though there does appear to be some reduced...
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  • 9
    QuantumClifford.jl

    QuantumClifford.jl

    Clifford circuits, graph states, and other quantum Stabilizer tools

    A Julia package for working with quantum stabilizer states and Clifford circuits that act on them. Graphs states are also supported. The package is already very fast for the majority of common operations, but there are still many low-hanging fruits performance-wise. See the detailed suggested readings & references page for background on the various algorithms.
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  • 10
    RuntimeGeneratedFunctions.jl

    RuntimeGeneratedFunctions.jl

    Functions generated at runtime without world-age issues or overhead

    RuntimeGeneratedFunctions are functions generated at runtime without world-age issues and with the full performance of a standard Julia anonymous function. This builds functions in a way that avoids eval. For technical reasons, RuntimeGeneratedFunctions needs to cache the function expression in a global variable within some module. This is normally transparent to the user, but if the RuntimeGeneratedFunction is evaluated during module precompilation, the cache module must be explicitly set...
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  • 11
    DynamicQuantities.jl

    DynamicQuantities.jl

    Lightweight + fast physical quantities in Julia

    DynamicQuantities defines a simple statically-typed Quantity type for Julia. Physical dimensions are stored as a value, as opposed to a parametric type, as in Unitful.jl. This can greatly improve both runtime performance, by avoiding type instabilities, and startup time, as it avoids overspecializing methods.
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  • 12
    Kinetic.jl

    Kinetic.jl

    Universal modeling and simulation of fluid mechanics upon ML

    Kinetic is a computational fluid dynamics toolbox written in Julia. It aims to furnish efficient modeling and simulation methodologies for fluid dynamics, augmented by the power of machine learning. Based on differentiable programming, mechanical and neural network models are fused and solved in a unified framework. Simultaneous 1-3 dimensional numerical simulations can be performed on CPUs and GPUs.
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  • 13
    Gaius.jl

    Gaius.jl

    Divide and Conquer Linear Algebra

    Gaius.jl is a multi-threaded BLAS-like library using a divide-and-conquer strategy to parallelism, and built on top of the fantastic LoopVectorization.jl. Gaius spawns threads using Julia's depth-first parallel task runtime and so Gaius's routines may be fearlessly nested inside multi-threaded Julia programs. Gaius is not stable or well-tested. Only use it if you're adventurous.
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  • 14
    Circuitscape.jl

    Circuitscape.jl

    Algorithms from circuit theory to predict connectivity

    Circuitscape is an open-source program that uses circuit theory to model connectivity in heterogeneous landscapes. Its most common applications include modeling the movement and gene flow of plants and animals, as well as identifying areas important for connectivity conservation. The new Circuitscape is built entirely in the Julia language, a new programming language for technical computing. Julia is built from the ground up to be fast. As such, this offers a number of advantages over the...
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  • 15
    MLJBase.jl

    MLJBase.jl

    Core functionality for the MLJ machine learning framework

    Repository for developers that provides core functionality for the MLJ machine learning framework. MLJ is a Julia framework for combining and tuning machine learning models. This repository provides core functionality for MLJ.
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  • 16
    RCall.jl

    RCall.jl

    Call R from Julia

    R is a language for statistical computing and graphics that has been around for a couple of decades and it has one of the most impressive collections of scientific and statistical packages of any environment. Recently, the Julia language has become an attractive alternative because it provides the remarkable performance of a low-level language without sacrificing the readability and ease of use of high-level languages. However, Julia still lacks the depth and scale of the R package environment...
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  • 17
    Metal.jl

    Metal.jl

    Metal programming in Julia

    With Metal.jl it's possible to program GPUs on macOS using the Metal programming framework. The package is a work in progress. There are bugs, functionality is missing, and performance hasn't been optimized. Expect to have to make changes to this package if you want to use it. PRs are very welcome. These requirements are fairly strict, and are due to our limited development resources (manpower, hardware). Technically, they can be relaxed. If you are interested in contributing to this, see...
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  • 18
    Mousetrap.jl

    Mousetrap.jl

    Finally, a GUI Engine made for Julia

    Mousetrap is a GUI library designed for Julia. It fully wraps GTK4 (which is written in C), vastly simplifying its interface to improve ease of use without sacrificing flexibility. It aims to give developers of all skill levels the tools to start creating complex GUI applications with little time and effort while taking full advantage of Julia's idiosyncrasies.
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  • 19
    ReverseDiff

    ReverseDiff

    Reverse Mode Automatic Differentiation for Julia

    ReverseDiff is a fast and compile-able tape-based reverse mode automatic differentiation (AD) that implements methods to take gradients, Jacobians, Hessians, and higher-order derivatives of native Julia functions (or any callable object, really). While performance can vary depending on the functions you evaluate, the algorithms implemented by ReverseDiff generally outperform non-AD algorithms in both speed and accuracy.
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  • 20
    Interpolations.jl

    Interpolations.jl

    Fast, continuous interpolation of discrete datasets in Julia

    This package implements a variety of interpolation schemes for the Julia language. It has the goals of ease of use, broad algorithmic support, and exceptional performance. Currently, this package supports B-splines and irregular grids. The API has been designed with the intent to support more options. Initial support for Lanczos interpolation was recently added. Pull requests are more than welcome! It should be noted that the API may continue to evolve over time.
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  • 21
    Spring Batch

    Spring Batch

    Spring Batch is a framework for writing batch applications using Java

    A lightweight, comprehensive batch framework designed to enable the development of robust batch applications vital for the daily operations of enterprise systems. Spring Batch provides reusable functions that are essential in processing large volumes of records, including logging/tracing, transaction management, job processing statistics, job restart, skip, and resource management. It also provides more advanced technical services and features that will enable extremely high-volume and high...
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  • 22
    Vortex

    Vortex

    The LLVM of columnar file formats

    Vortex is a high-performance toolkit designed for working with compressed Apache Arrow arrays, providing functionality for in-memory, on-disk, and over-the-wire data handling. It aims to be an advanced successor to Apache Parquet, offering dramatically faster random access reads and scans, while maintaining similar compression ratios. Vortex's modular design allows for extensibility, enabling developers to implement custom encodings for efficient data management, particularly for large-scale...
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  • 23
    TIGRE

    TIGRE

    TIGRE: Tomographic Iterative GPU-based Reconstruction Toolbox

    TIGRE is an open-source toolbox for fast and accurate 3D tomographic reconstruction for any geometry. Its focus is on iterative algorithms for improved image quality that have all been optimized to run on GPUs (including multi-GPUs) for improved speed. It combines the higher-level abstraction of MATLAB or Python with the performance of CUDA at a lower level in order to make it both fast and easy to use. TIGRE is free to download and distribute: use it, modify it, add to it, and share it. Our...
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  • 24
    PowerSimulations.jl

    PowerSimulations.jl

    Julia for optimization simulation and modeling of PowerSystems

    PowerSimulations.jl is a Julia package for power system modeling and simulation of Power Systems operations. Provide a flexible modeling framework that can accommodate problems of different complexity and at different time scales. Streamline the construction of large-scale optimization problems to avoid repetition of work when adding/modifying model details. Exploit Julia's capabilities to improve computational performance of large-scale power system quasi-static simulations. The flexible...
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  • 25
    ForwardDiff.jl

    ForwardDiff.jl

    Forward Mode Automatic Differentiation for Julia

    ForwardDiff implements methods to take derivatives, gradients, Jacobians, Hessians, and higher-order derivatives of native Julia functions (or any callable object, really) using forward mode automatic differentiation (AD). While performance can vary depending on the functions you evaluate, the algorithms implemented by ForwardDiff generally outperform non-AD algorithms (such as finite-differencing) in both speed and accuracy. Functions like f which map a vector to a scalar are the best case...
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