Search Results for "computations" - Page 2
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Showing 70 open source projects for "computations"
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Neural Tangents
Fast and Easy Infinite Neural Networks in Python
...The library closely mirrors JAX’s stax API while extending it to return a kernel_fn alongside init_fn and apply_fn, enabling drop-in workflows for kernel computation. Kernel evaluation is highly optimized for speed and memory, and computations can be automatically distributed across accelerators with near-linear scaling. -
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ZoKrates
A toolbox for zkSNARKs on Ethereum
...One particular family of ZKPs is described as zero-knowledge Succinct Non-interactive ARguments of Knowledge, a.k.a. zkSNARKs. zkSNARKs are the most widely used zero-knowledge protocols, with the anonymous cryptocurrency Zcash and the smart-contract platform Ethereum among the notable early adopters. Ethereum runs computations on all nodes of the network, resulting in high costs, limits in complexity, and low privacy. zkSNARKs have been enabling to only verify computations on-chain for a fraction of the cost of running them, but are hard to grasp and work with. -
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M.O.R.T.A.L.
The M.O.R.T.A.L. programming language
...It is meant to take the best features of multiple paradigms and combine them all into a single, easy-to-use language, suitable for professionals and hobbyists alike. (The basic OOP paradigm, with metaprogramming features, will be implemented first.) Its primary goal is to allow very heavy computations to be performed efficiently and easily, even by scientists from other fields than computer science. For more information about the language, see the Wiki. -
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Jadecy
Java lib to compute (code) deps, SCCs, and cycles (Johnson algorithm).
...API entry point for Java code dependencies is the Jadecy class, or DepUnit that makes use of it and is designed for unit tests. API entry point for general graph computations is the net.jadecy.graph package. Requires Java 5 or later. Also available on github: https://github.com/jeffhain/jadecy -
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vue-virtual-scroller
Blazing fast scrolling for any amount of data
...The Dynamic Scroller automatically "discovers" item dimensions as it renders new items during scrolling. DynamicScrollerItem must wrap each item in a DynamicScroller to handle size computations. IdState is a mixin that ease the local state management in reused components inside a RecycleScroller. RecycleScroller is a virtual scroller that only renders the visible items. As the user scrolls, RecycleScroller reuses all components and DOM nodes to maintain optimal performance. -
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Gym
Toolkit for developing and comparing reinforcement learning algorithms
Gym by OpenAI is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents, everything from walking to playing games like Pong or Pinball. Open source interface to reinforce learning tasks. The gym library provides an easy-to-use suite of reinforcement learning tasks. Gym provides the environment, you provide the algorithm. You can write your agent using your existing numerical computation library, such as TensorFlow or Theano. It makes no... -
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Security Code Scan
Vulnerability Patterns Detector for C# and VB.NET
...Other editors that support Roslyn-based analyzers like Rider or OmniSharp should work too. Security Code Scan (SCS) is not a Linter. It is a real static analysis tool that does extensive computations. Thus installing it as a Visual Studio extension or NuGet package will slow down your Visual Studio IDE. -
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Arraymancer
A fast, ergonomic and portable tensor library in Nim
Arraymancer is a tensor and deep learning library for the Nim programming language, designed for high-performance numerical computations and machine learning applications. -
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Ultra Runner
Ultra fast monorepo script runner and build tool
Ultra Runner is a high-performance task runner for monorepos. It optimizes package execution, dependency management, and caching to improve speed and efficiency when running scripts across multiple projects. -
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Accelerate
Embedded language for high-performance array computations
Data.Array.Accelerate defines an embedded language of array computations for high-performance computing in Haskell. Computations on multi-dimensional, regular arrays are expressed in the form of parameterized collective operations (such as maps, reductions, and permutations). These computations are online-compiled and executed on a range of architectures. Accelerate is a free, general-purpose, open-source library that simplifies the process of developing software that targets massively parallel architectures including multicore CPUs and GPUs. ... -
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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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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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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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STXXL is an implementation of the C++ standard template library STL for external memory (out-of-core) computations, containers, and algorithms that can process huge volumes of data that only fit on disks.
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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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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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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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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. ... -
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Arageli is a C++ library for computations in arithmetic, algebra, geometry, linear and integer linear programming. Arageli provides routines and classes that support precise, i.e. symbolic or algebraic, computations.
