Search Results for "computations" - Page 4
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Showing 162 open source projects for "computations"
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Traffic
Intersection is a OFA implementation modeling a traffic intersection.
...This simulation grew out of my disgust with driving to and from work. The simulation currently models only a single intersection. I had envisioned that I would expand the simulation to an array of 10x10 intersections. However, computations for a single intersection are quite time consuming. So unless I can figure out a more efficient computation or modeling mechanism, I am less inclined to pursue the multiple intersection modeling. -
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CrypTen
A framework for Privacy Preserving Machine Learning
CrypTen is a research framework developed by Facebook Research for privacy-preserving machine learning built directly on top of PyTorch. It provides a secure and intuitive environment for performing computations on encrypted data using Secure Multiparty Computation (SMPC). Designed to make secure computation accessible to machine learning practitioners, CrypTen introduces a CrypTensor object that behaves like a regular PyTorch tensor, allowing users to seamlessly apply automatic differentiation and neural network operations. Its design mirrors PyTorch’s modular and library-based structure, enabling flexible experimentation, debugging, and model development. ... -
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TensorFlow Haskell
Haskell bindings for TensorFlow
The tensorflow-haskell package provides Haskell-language bindings for TensorFlow, giving Haskell developers the ability to build and run computation graphs, machine learning models, and leverage TensorFlow's ecosystem—though it is not an official Google release. As an expedient we use docker for building. Once you have docker working, the following commands will compile and run the tests. Run the install_macos_dependencies.sh script in the tools/ directory. The script installs dependencies... -
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Tensor Algebra Compiler
The Tensor Algebra Compiler (taco) computes sparse tensor expressions
...TACO can be used to implement sparse linear and tensor algebra applications in a wide range of domains. TACO supports a wide range of sparse (and dense) linear/tensor algebra computations, from simpler ones like sparse matrix-vector multiplication to more complex ones like MTTKRP on higher-order sparse tensors. Tensors can be stored in a variety of storage formats, including commonly-used sparse matrix and tensor formats like CSR and COO as well as specialized formats like CSF. Under the hood, TACO employs a novel compiler-based technique to generate kernels that are optimized for the computations you want to perform. ... -
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Prometheus Spec
Censorship-resistant trustless state channels for machine learning
...With the recent rise in popularity of Bitcoin as a censorship-resistant financial and transactional system a new technological field of blockchain and its applications appeared. This work addresses the problem of computational integrity proofs (correctness of the actual computations) made by some non-trusted (anonymous) third party without repeating the whole volume of the actual computing. The issue is usually addressed by use of probabilistically checkable proofs (PCP), however, such simple approach leave untouched the question of coupling the payments for the consumed computational resources with the actual proof. ... -
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brain.js
GPU accelerated Neural networks in JavaScript for Browsers
...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. -
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Stampede
The ToroDB solution to provide better analytics on top of MongoDB
Stampede is a high-performance cache stampede prevention library designed to mitigate excessive cache misses in distributed caching systems. It helps avoid the "thundering herd" problem, where multiple requests simultaneously trigger expensive computations when a cache entry expires. Stampede manages cache expiration intelligently, ensuring that only one request regenerates a missing cache entry while others wait for the updated value. -
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Prepack
A JavaScript bundle optimizer
...Prepack is still in an early development stage and not ready for production use just yet. Please try it out, give feedback, and help fix bugs. Prepack is a tool that optimizes JavaScript source code: Computations that can be done at compile-time instead of run-time get eliminated. Prepack replaces the global code of a JavaScript bundle with equivalent code that is a simple sequence of assignments. This gets rid of most intermediate computations and object allocations. Prepack operates at the AST level, using Babel to parse and generate JavaScript source code. ... -
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X10
Performance and Productivity at Scale
...This model introduces two key concepts -- places and asynchronous tasks -- and a few mechanisms for coordination. With these, APGAS can express both regular and irregular parallelism, message-passing-style and active-message-style computations, fork-join and bulk-synchronous parallelism. Both its modern, type-safe sequential core and simple programming model for concurrency and distribution contribute to making X10 a high-productivity language in the HPC and Big Data spaces. User productivity is further enhanced by providing tools such as an Eclipse-based IDE (X10DT). ... -
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NimTorch
PyTorch - Python + Nim
NimTorch is a deep learning library for the Nim programming language, providing bindings to PyTorch for efficient tensor computations and neural network functionalities. -
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ampclib
Arithmetic Multlple Precision Computation Library
ampclib is a simple to use platform independed C++ library for arithmetic multiple precision computations with a ritch and self explaining interface. It provides number theoretic functions and primality tests. The ampclib consists of three classes: +Integer (multiple precision integers) +Rational (multiple precision rational numbers using the Integer class) +Primes (prime number computations and number theoretic functions for unsigned 32 bit integers) The latest release contains optimizations and bug fixes. -
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Tiramisu
Polyhedral compiler for expressing fast and portable data algorithms
Tiramisu is a compiler for expressing fast and portable data parallel computations. It provides a simple C++ API for expressing algorithms (Tiramisu expressions) and how these algorithms should be optimized by the compiler. Tiramisu can be used in areas such as linear and tensor algebra, deep learning, image processing, stencil computations and machine learning. The Tiramisu compiler is based on the polyhedral model thus it can express a large set of loop optimizations and data layout transformations. ... -
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RadiationHelper
Alpha, Beta, Gamma measurements and Nuclide exposure
RadiationHelper is a data analysis tool for : 1. gross alpha and beta radiation measurement and detector calibration using experimental data (counts acquired by alpha-beta devices). 2. gamma spectroscopy measurements and detector calibration using experimental data (spectra acquired by acquisition software such as Assayer, Gamma Vision, Maestro) 3. gross alpha,beta, gamma detector efficiencies and gamma peak efficiency can be theoretical computed using Monte-Carlo simulation technique for radiation transport (based on EGSnrc toolkit) 4.dose assessment in human body exposed to radiations from nuclides in several common scenarios such as air exposure, water submersion, ground surface, internal ingestion or inhalation. 5. quick dosimetry and shielding computations. It is platform independent (written entirely in Java). Source code included in jar files! Also, available on GitHub: https://github.com/ZiliasTheSaint/RadiationHelper.git Checkout for dependent modules! -
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A package for computations with finite automata (rooted tree automorphisms) for the GAP system, http://www.gap-system.org.
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cquery
C/C++ language server supporting multi-million line code base
...It is tested and designed for large codebases like Chromium. cquery provides accurate and fast semantic analysis without interrupting workflow. cquery implements almost the entire language server protocol and provides some extra features to boot. cquery is able to respond to queries quickly because it caches a huge amount of information. When a request comes in, cquery just looks it up in the cache without running many computations. As a result, there's a large memory overhead. For example, a full index of Chrome will take about 10gb of memory. If you exclude v8, webkit, and third_party, it goes down to about 6.5gb. -
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Visibility.js
Wrapper for the Page Visibility API
...Its main purpose is to let web applications adapt behavior depending on whether the page is actually being viewed — for example, pausing animations, postponing heavy computations, or stopping unnecessary network requests when the user switches to another tab. The library hides browser vendor-prefixes and normalizes visibility events so you don’t have to manage cross-browser quirks yourself. On top of simple visibility detection, Visibility.js adds useful helpers such as a timer function that only runs when the page is visible. ... -
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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.
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Vaex
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python
...Visualization is done using histograms, density plots and 3d volume rendering, allowing interactive exploration of big data. Vaex uses memory mapping, zero memory copy policy and lazy computations for best performance (no memory wasted). Cut development cut development time by 80%. Your prototype is your solution. Create automatic pipelines for any model. -
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FastRoute
Fast request router for PHP
...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. ... -
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...This project provides tools for manipulate and convert the lata files. This project is part of the VisIt plugin reader. The Snorky3D sofware is presented in the following conference communication: Visualisation of CFD computations: millions of particles in real time with Snorky3D Visu 2012, september 2012, Paris, France http://visu2012.imag.fr/articles/mathieu.pdf
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PolyBench/C 4.2 Copyright (c) 2011-2016 the Ohio State University. Contact: Louis-Noel Pouchet <pouchet@cse.ohio-state.edu> Tomofumi Yuki <tomofumi.yuki@inria.fr> PolyBench is a benchmark suite of 30 numerical computations with static control flow, extracted from operations in various application domains (linear algebra computations, image processing, physics simulation, dynamic programming, statistics, etc.). PolyBench features include: - A single file, tunable at compile-time, used for the kernel instrumentation. It performs extra operations such as cache flushing before the kernel execution, and can set real-time scheduling to prevent OS interference...
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Construct2D
COmputational fluid dyNamics STRUctured grid CreaTor for 2D airfoils
Construct2D is a grid generator designed to create 2D grids for CFD computations on airfoils. The grids are generated in Plot3D format. The only required input file is the set of coordinates defining the airfoil geometry, using the same format as XFoil, the popular vortex-panel code for airfoil analysis. Construct2D can create grids with O topology (recommended for airfoils with a blunt trailing edge) or C topology (recommended for airfoils with a sharp trailing edge). -
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Matlab/Octave Rotations Library
Library for working with 3D rotations in Matlab/Octave
The Matlab/Octave rotations library is a collection of functions, bundled as m-scripts, that address computations and numerical handling of rotations in 3D Euclidean space. The rotation representations that are supported are rotation matrices (Rotmat), Quaternions (Quat), intrinsic ZYX Euler angles (Euler), fused angles (Fused) and tilt angles (Tilt). Operations such as composition, inversion, ZYX yaw extraction, fused yaw extraction, random generation, equality detection, vector rotation and much more have been implemented for each rotation representation. ... -
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Rotations Conversion Library
Library for working with 3D rotations in C++
The Rotations Conversion Library (RCL) is a collection of C++ functions that address common computations and numerical handling of rotations in 3D Euclidean space, including support for rotation matrices (`Rotmat`), Quaternions (`Quat`), intrinsic ZYX Euler angles (`Euler`), fused angles (`Fused`) and tilt angles (`Tilt`). In addition to the core competency of being able to convert between each of the representations, operations such as inversion, ZYX yaw extraction, fused yaw extraction, renormalisation, equality detection, vector rotation and much more have been implemented. ... -
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Haxl
Haskell library that simplifies access to remote data
...Haxl can automatically batch multiple requests to the same data source, request data from multiple data sources concurrently, cache previous requests, and memoize computations. Having all this handled for you behind the scenes means that your data-fetching code can be much cleaner and clearer than it would otherwise be if it had to worry about optimizing data-fetching. To use Haxl in your own application, you will likely need to build one or more data sources: the thin layer between Haxl and the data that you want to fetch, be it a database, a web API, a cloud service, or whatever. ...
