Local process cluster management for distributed computation
minimal module for launching and managing a compute cluster
The engine that powers scroll-into-view-if-needed
Generates CRC hashes for strings - for use by node redis clients to determine key slots.
AWS SDK for JavaScript Ecs Client for Node.js, Browser and React Native
Find the position of grapheme cluster breaks in a string
Google Compute Engine Client Library for Node.js
Computes the greatest common divisor (gcd).
Computes the least common multiple (lcm).
JavaScript SDK and CLI for building JavaScript applications on [Fastly Compute](https://www.fastly.com/products/edge-compute/serverless).
Fast nd point clustering.
Computes the dot product between two numeric arrays.
Client for prometheus
A generated SDK for ComputeManagementClient.
Computes the L2 norm (Euclidean norm) of an array of values.
React-leaflet-cluster is a plugin for react-leaflet. A wrapper component of Leaflet.markercluster.
Computes the cosine similarity between two arrays.
Cluster management for puppeteer
The luma.gl core Device API
Pure Javascript implementation of the BLAKE2b and BLAKE2s hash functions
Symbolic computing and numeric evaluations for JavaScript and Node.js
Group points into clusters based on their spatial proximity or properties.
* implements render engine's interface with WebGPU/WebGL
Compute a diff of two Slate documents
Zero configuration job scheduler for computer clusters
scbi_queue_system (SQS) handles a simple queue of jobs executions over multiple machines (clustered installation) or your own personal computer.
scbi_mapreduce brings parallel and distributed computing capabilities to your code, with a very easy to use framework that allows you to exploit your clustered or cloud computational resources.
Peplum allows you to easily combine the resources of multiple machines and build a Beowulf (or otherwise) cluster/super-computer.
RubyVor provides efficient computation of Voronoi diagrams and Delaunay triangulation for a set of Ruby points. It is intended to function as a complemenet to GeoRuby. These structures can be used to compute a nearest-neighbor graph for a set of points. This graph can in turn be used for proximity-based clustering of the input points.
RubyVor provides efficient computation of Voronoi diagrams and Delaunay triangulation for a set of Ruby points. It is intended to function as a complemenet to GeoRuby. These structures can be used to compute a nearest-neighbor graph for a set of points. This graph can in turn be used for proximity-based clustering of the input points.
Filestore instances are fully managed NFS file servers on Google Cloud for use with applications running on Compute Engine virtual machines (VMs) instances or Google Kubernetes Engine clusters.
Define your project in terms of blocks, configurations, tests, and modes. Install or Create recipes and/or plugins to define actions, compute clusters, and tools for simulation, synthesis, or anything else. Run your actions, test_lists, or tests in parallel, with dependencies, on a cluster, or locally. Share your recipes and plugins with people down the hall and around the world.
RubyVor provides efficient computation of Voronoi diagrams and Delaunay triangulation for a set of Ruby points. It is intended to function as a complemenet to GeoRuby. These structures can be used to compute a nearest-neighbor graph for a set of points. This graph can in turn be used for proximity-based clustering of the input points.
Pampa is a Ruby library for async & distributing computing providing the following features: - cluster-management with dynamic reconfiguration (joining and leaving nodes); - distribution of the computation jobs to the (active) nodes; - error handling, job-retry and fault tolerance; - fast (non-direct) communication to ensure realtime capabilities. The Pampa framework may be widely used for: - large scale web scraping with what we call a "bot-farm"; - payments processing for large-scale ecommerce websites; - reports generation for high demanded SaaS platforms; - heavy mathematical model computing; and any other tasks that requires a virtually infinite amount of CPU computing and memory resources. Find documentation here: https://github.com/leandrosardi/pampa
scbi_distributed_blast is a simple distribution mechanism for blast+ made on top of scbi_mapreduce. With scbi_distributed_blast you can perform distributed blasts using a cluster, a set of machines of your network or your own multi-core personal computer. It uses the same blast+ that you have already installed.
The library for mathematical optimization in Ruby is designed to help solve many problems in the computational, financial, social, and energy fields and, in theory, should include components of game theory, combinatorics, probability theory, linear and nonlinear optimization, cluster, regression, and other analysis.
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