Search Results for "computations"

...All changes to and uses of your data are tracked at runtime, building a dependency tree that captures all relations between state and output. This guarantees that computations depending on your state, like React components, run only when strictly needed. There is no need to manually optimize components with error-prone and sub-optimal techniques like memoization and selectors.

dispy is a generic and comprehensive, yet easy to use framework for creating and using compute clusters to execute computations in parallel across multiple processors in a single machine (SMP), among many machines in a cluster, grid or cloud. dispy is well suited for data parallel (SIMD) paradigm where a computation (Python function or standalone program) is evaluated with different (large) datasets independently. dispy supports public / private / hybrid cloud computing, fog / edge computing.

...However, if you run into problems, this means prebuilt binaries are not able to download from GitHub repositories and you might need to build it yourself. Brain.js is super simple to use. You do not need to know Neural Networks in detail to work with this. Brain.js performs computations using GPU and gracefully fallback to pure JavaScript when GPU is not available. Brain.js provides multiple neural network implementations as different neural nets can be trained to do different things well. Easily export and import trained models using JSON format or as a function. Host pre-trained models on your website easily.

Slimgrid is a Java library for grid computations which is lighter than other ones (JPPF, Hadoop, ...). The main design goals are: minimalism, simplicity, pervasiveness. If you need to grab something which does not require you to comprehend massive and complex API's, do exhaustive configurations and installations, is robust and reliable, uses just one port for all management and communication, then SlimGrid is the right choice.

...Firstly, while writing a PHP extension is obviously a lot of fun, it is unlikely to be particularly beneficial in terms of performance unless the code involves computations in tight loops. Porting “normal” components like routers to C is usually a big waste of time. You can get much better results by doing a few small improvements on the algorithmic side. For the same reason I’m not a big fan of things like Phalcon, i.e. PHP frameworks written as a C extension. You can get good performance by using an appropriate application design (that is not massively overengineered) and still retain the flexibility of keeping everything in PHP. ...

PUPS/P3 facilitates development of multi-process multi-host computations by providing tools to emulate colonies of homeostatic organisms. It permits persistent computation, homeostatic resource protection, and asychronous interprocess communication.

A transparent network messaging system for offloading computations to other possibly more capable machines when they are available. The intended use of the system is for when the results of a computation aren't needed immediately.

Tiny Distributed Computing Library is an easy to use cross-platform library for performing distributed computations. It is written in C++ and designed with good performance and modularity in mind.

glomp is an open source multipipe OpenGL library. Its intent is to automatically distribute 3D graphics computations over multiple graphics card on the same machine.

This is a library for parallelizing flow data computations on Cell processors.

The Advanced Network Traffic Analysis Research and Exploration Suite (ANTARES) is a toolkit for working with flow attributes - computations that can be used to distinguish between different uses of the network, even without using packet payloads.

The aim of the OpenGrid project is to enable personal high-performance grid computations. More specific, issues of configuration, deployment, controlling and monitoring of embarrassingly parallel computations are addressed.