Search Results for "compute" - Page 4
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Showing 135 open source projects for "compute"
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MACE
Deep learning inference framework optimized for mobile platforms
Mobile AI Compute Engine (or MACE for short) is a deep learning inference framework optimized for mobile heterogeneous computing on Android, iOS, Linux and Windows devices. Runtime is optimized with NEON, OpenCL and Hexagon, and Winograd algorithm is introduced to speed up convolution operations. The initialization is also optimized to be faster. -
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git-sizer
Compute various size metrics for a Git repository
git-sizer computes various size metrics for a local Git repository, flagging those that might cause you problems or inconvenience. Is the repository too big overall? Ideally, Git repositories should be under 1 GiB, and (without special handling) they start to get unwieldy over 5 GiB. Big repositories take a long time to clone and repack, and take a lot of disk space. Avoid storing generated files (e.g., compiler output, JAR files) in Git. It would be better to regenerate them when necessary,... -
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Intel compute-runtime
Intel® Graphics Compute Runtime
The Intel(R) Graphics Compute Runtime for oneAPI Level Zero and OpenCL(TM) Driver is an open source project providing compute API support (Level Zero, OpenCL) for Intel graphics hardware architectures (HD Graphics, Xe). -
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Terraform Inventory
Terraform State, Ansible dynamic inventory
This is a little Go app that generates a dynamic Ansible inventory from a Terraform state file. It allows one to spawn a bunch of instances with Terraform, then (re-)provision them with Ansible. This library is stable, but I've been neglecting it somewhat on account of no longer using Ansible at work. On OSX, install it with Homebrew. Alternatively, you can download a release suitable for your platform and unzip it. Make sure the terraform-inventory binary is executable, and you're ready to... -
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TensorFlow MacOS
TensorFlow for macOS 11.0+ accelerated using Apple's ML Compute
This repository provided a pre-release of TensorFlow and TensorFlow Addons tailored for macOS 11+ with native hardware acceleration via Apple’s ML Compute, supporting both Apple Silicon (M1) and Intel Macs. It shipped ready-made Python 3.8 wheels and install scripts so developers could quickly get an accelerated stack running without building from source. As TensorFlow added a Metal PluggableDevice path, the project directed users toward using Apple’s tensorflow-metal to get GPU acceleration on Mac directly through Metal. ... -
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constructs-go
Golang bindings for constructs
...A construct can represent a single AWS resource, such as an Amazon Simple Storage Service (Amazon S3) bucket, or it can be a higher-level abstraction consisting of multiple AWS related resources. Examples of such components include a worker queue with its associated compute capacity, or a scheduled job with monitoring resources and a dashboard. The AWS CDK includes a collection of constructs called the AWS Construct Library, containing constructs for every AWS service. -
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Amazon SageMaker Examples
Jupyter notebooks that demonstrate how to build models using SageMaker
...If you’re new to SageMaker we recommend starting with more feature-rich SageMaker Studio. It uses the familiar JupyterLab interface and has seamless integration with a variety of deep learning and data science environments and scalable compute resources for training, inference, and other ML operations. Studio offers teams and companies easy on-boarding for their team members, freeing them up from complex systems admin and security processes. Administrators control data access and resource provisioning for their users. Notebook Instances are another option. They have the familiar Jupyter and JuypterLab interfaces that work well for single users, or small teams where users are also administrators. ... -
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progrep
Utility to show live progress, status & stats for running simulations
progrep is a command-line tool (Linux) to show live progress report, status & stats of a running simulation or compute job that executes a given number of iterations. It shows % completed, time remaining, time elapsed, number of threads, MPI_Rank(if any), CPU usage & speed (FPS). The FPS measures may be used in benchmarking, e.g. while optimizing HPC algorithms for performance. progrep supports both single-threaded and parallel (multicore/multinode - e.g. -
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Sparse Attention
"Generating Long Sequences with Sparse Transformers" examples
...Though archived, it remains a key reference for efficient transformer research, influencing many later architectures that aim to extend sequence length while reducing compute. -
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PerfKit Benchmarker
PerfKit Benchmarker (PKB) contains a set of benchmarks
...It simplifies the process of running complex benchmarks by providing unified command-line workflows that handle resource provisioning, execution, and result collection. The framework includes a comprehensive set of predefined benchmarks covering areas such as compute, storage, networking, and distributed systems workloads. It is widely used by researchers, engineers, and organizations to evaluate cloud architectures and make informed infrastructure decisions. -
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Higher
higher is a pytorch library
higher is a specialized library designed to extend PyTorch’s capabilities by enabling higher-order differentiation and meta-learning through differentiable optimization loops. It allows developers and researchers to compute gradients through entire optimization processes, which is essential for tasks like meta-learning, hyperparameter optimization, and model adaptation. The library introduces utilities that convert standard torch.nn.Module instances into “stateless” functional forms, so parameter updates can be treated as differentiable operations. ... -
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AdaNet
Fast and flexible AutoML with learning guarantees
AdaNet is a TensorFlow framework for fast and flexible AutoML with learning guarantees. AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet builds on recent AutoML efforts to be fast and flexible while providing learning guarantees. Importantly, AdaNet provides a general framework for not only learning a neural network architecture but also for learning to the ensemble to obtain even better models. At each... -
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java-string-similarity
Implementation of various string similarity and distance algorithms
...A dozen of algorithms (including Levenshtein edit distance and sibblings, Jaro-Winkler, Longest Common Subsequence, cosine similarity etc.) are currently implemented. The main characteristics of each implemented algorithm are presented below. The "cost" column gives an estimation of the computational cost to compute the similarity between two strings of length m and n respectively. If the alphabet is finite, it is possible to use the method of four russians (Arlazarov et al. "On economic construction of the transitive closure of a directed graph", 1970) to speedup computation. This was published by Masek in 1980 ("A Faster Algorithm Computing String Edit Distances"). -
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GraalVM
Run programs faster anywhere
...Compile applications into small self-contained native binaries. Seamlessly use multiple languages and libraries. Advanced optimizing compiler that generates fast lean code which requires fewer compute resources. Native binaries start up instantly and deliver peak performance with no warm up time. Leverage the best features and libraries of popular languages in a single app with no overhead. Debug, monitor, profile, and optimize resource consumption in Java and across multiple languages. Enterprise version provides all Community features along with higher performance and enhanced security. ... -
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The Fission CL
Command-line interface for Fission
The Fission CLI is now part of the main fission-suite/fission repo. We construct identity, data, and compute solutions for the future of the Internet. Users want data ownership and privacy without compromising on a seamless experience. You want to build a resilient application that is fast, cost-effective, and efficient. We build local-first and edge computing tools that make all of this possible. Fission builds open source protocols and managed solutions that empower developers to construct humane software applications. -
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Synthclipse
GLSL shader prototyping tool based on Eclipse IDE.
Synthclipse is a GLSL shader prototyping tool. It makes possible to fast develop all kinds of shaders: Fragment (FS), Vertex (VS), Geometry (GS), Tessellation (TS) and Compute (CS). Shader development can be done using, compatible with Fragmentarium and Shadertoy (but limited to FS and VS), Fragx shaders or by using fully featured JavaScript JSX scripts. The JSX API is consistent with WebGL but in fact exposes complete OpenGL 4+ API. To install Synthclipse one can download prepacked Eclipse with Synthclipse feature (see "Files" section above) or update an existing Eclipse using the following Update Site: https://kamil-kolaczynski.github.io/synthclipse/update/ Prepacked version has one advantage: it has nice console logs coloring since it shipped with Grep Console plugin ( https://marketplace.eclipse.org/content/grep-console ) that is configured specially for Synthclipse logs. -
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"CUDA Templates" is a collection of C++ template classes and functions which provide a consistent interface to NVidia's "Compute Unified Device Architecture" (CUDA), hiding much of the complexity of the underlying CUDA functions from the programmer.
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Kalibr Allan
IMU Allan standard deviation charts
...While manufacturers typically provide “white noise” values in IMU datasheets, the bias instability and random walk parameters must be determined experimentally. This project enables users to compute those values using Allan variance analysis from recorded IMU data. The workflow involves recording IMU measurements with the device stationary, converting ROS bag files into MATLAB-compatible formats, and then running MATLAB scripts to generate Allan deviation plots. These plots are analyzed to determine noise density and random walk parameters for both gyroscopes and accelerometers. ... -
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Video Nonlocal Net
Non-local Neural Networks for Video Classification
...Efficient implementations keep memory and compute manageable so the blocks can be added without rewriting the entire backbone. The result is a practical, drop-in mechanism for upgrading purely local video models into context-aware networks with strong benchmark performance. -
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datastat
Simple data statistics readily from the command-line
datastat is a command-line tool that allows one to compute simple statistics over columns of numeric data in text files by aggregating rows on the basis of the values of the specified key columns. -
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properties
another c#-like property accessor for c++11 and above.
A property is a member that provides a flexible mechanism to read, write, or compute the value of a private field. Properties can be used as if they are public data members, but they are actually special methods called accessors. This enables data to be accessed easily and still helps promote the safety and flexibility of methods. * Github repository : https://github.com/gammasoft71/properties * Homepage : https://gammasoft71.wixsite.com/properties * Reference guide : https://codedocs.xyz/gammasoft71/properties/ * Examples : https://github.com/gammasoft71/properties/tree/master/examples -
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IPS Framework
A simple Python framework for loosely-coupled multiphysics simulations
...One of the novel features of the IPS framework is its ability to support parallelism at multiple levels: components can launch individual parallel tasks, and also launch multiple tasks concurrently. The framework can execute multiple components concurrently, and even multiple simulations, all within the same pool of compute nodes. -
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aframe-react
Build virtual reality experiences with A-Frame and React
...React wastes a lot of cycles and incurs a lot of memory garbage. aframe-react is often abused where it is too easy to place 3D/real-time logic at the React layer, causing poor performance (e.g., doing React renders on ticks). aframe-react applications frequently ignore the prescribed ECS framework of A-Frame. Internally, React does tons of computation to compute what changed, and flushes it to the entire application. It is apparent React ecosystem does not care much about memory as most examples allocate functions and objects in the render method, and where immutables are popular. -
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SoftPixel Engine
Realtime 3D engine for game development
The SoftPixel Engine is an OpenSource high level realtime 3D engine for C++ (GNU C++ & VisualC++). It supports Direct3D11, Direct3D9, OpenGL 1.1 - 4.1, OpenGL|ES 1.1 and OpenGL|ES 2.0 and runs on Windows, Linux, Android and iOS. -
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WorkingWiki is a MediaWiki extension that makes a wiki into a source-code repository, IDE, and compute server. It has special support for LaTeX projects, including sophisticated translation to HTML for display within the wiki page.
