Search Results for "cpu" - Page 4
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Showing 323 open source projects for "cpu"
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Next-Gen Encryption for Post-Quantum Security | CLEAR by Quantum KnightCLEAR by Quantum Knight is a FIPS-140-3 validated encryption SDK engineered for enterprises requiring top-tier security. Offering robust post-quantum cryptography, CLEAR secures files, streaming media, databases, and networks with ease across over 30 modern platforms. Its compact design, smaller than a single smartphone image, ensures maximum efficiency and low energy consumption.
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Field Service+ for MS Dynamics 365 & SalesforceResco’s mobile solution streamlines your field service operations with offline work, fast data sync, and powerful tools for frontline workers, all natively integrated into Dynamics 365 and Salesforce.
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macOS (Dockur)
macOS inside a Docker container
dockur/macos packages a macOS virtual machine inside a Docker container using QEMU/KVM, making it easy to spin up a macOS environment on a Linux host. It provides sensible defaults for firmware, disk, and devices, plus a browser-accessible VNC console so you can complete installation and interact with the desktop remotely. Typical inputs—like environment variables and mounted volumes—control edition choice, storage persistence, and resource sizing, which makes runs repeatable and disposable.... -
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CrossDB
Ultra High-performance Lightweight Embedded and Server OLTP RDBMS
CrossDB is a ultra high-performance, lightweight embedded and server OLTP RDBMS. It is designed for high-performance scenarios where the main memory can hold the entire database. -
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Kubernetes Autoscaler
Autoscaling components for Kubernetes
...Supports several public cloud providers. Version 1.0 (GA) was released with kubernetes 1.8. Vertical Pod Autoscaler, a set of components that automatically adjust the amount of CPU and memory requested by pods running in the Kubernetes Cluster. Addon Resizer, a simplified version of vertical pod autoscaler that modifies resource requests of a deployment based on the number of nodes in the Kubernetes Cluster. -
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DoKit
A platform for the life cycle of pan-front-end product development
DoKit is a debugging and quality-of-experience toolkit for mobile (primarily Android) apps that provides an in-app overlay with tools for inspection, monitoring, and interaction. It offers features like CPU/memory monitoring, frame rate detection, network logging, view hierarchy inspection, and plugin support to expand capabilities. Developers can interactively explore UI layouts, measure layout times, simulate slow networks, or trace touch events—all while the app is running on the device. DoKit aims to shorten feedback loops by surfacing internal state and metrics in situ rather than relying solely on external logging or tooling. ... -
Rezku Point of SaleRezku is an all-inclusive ordering platform and management solution for all types of restaurant and bar concepts. You can now get a fully custom branded downloadable smartphone ordering app for your restaurant exclusively from Rezku.
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OpenCost
Cost monitoring for Kubernetes workloads and cloud costs
OpenCost is a vendor-neutral open-source project for measuring and allocating cloud infrastructure and container costs in real-time. Built by Kubernetes experts and supported by Kubernetes practitioners, OpenCost shines a light into the black box of Kubernetes spending. Flexible, customizable cost allocation and cloud resource monitoring for accurate showback, chargeback, and ongoing reporting. Dynamic asset pricing, through integrations with AWS, Azure, and GCP billing APIs as well as... -
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Face Alignment
2D and 3D Face alignment library build using pytorch
Detect facial landmarks from Python using the world's most accurate face alignment network, capable of detecting points in both 2D and 3D coordinates. Build using FAN's state-of-the-art deep learning-based face alignment method. For numerical evaluations, it is highly recommended to use the lua version which uses identical models with the ones evaluated in the paper. More models will be added soon. By default, the package will use the SFD face detector. However, the users can alternatively... -
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ArrayFire
ArrayFire, a general purpose GPU library
...Together we can fulfill The ArrayFire Mission under an excellent Code of Conduct that promotes a respectful and friendly building experience. Rigorous benchmarks and tests ensuring top performance and numerical accuracy. Cross-platform compatibility with support for CUDA, OpenCL, and native CPU on Windows, Mac, and Linux. Built-in visualization functions through Forge. -
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Bumblebee
Pre-trained Neural Network models in Axon
...First, add Bumblebee and EXLA as dependencies in your mix.exs. EXLA is an optional dependency but an important one as it allows you to compile models just-in-time and run them on CPU/GPU. -
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Apache SkyWalking Java Agent
The Java agent for Apache SkyWalking
SkyWalking-Java: The Java Agent for Apache SkyWalking, which provides native tracing/metrics/logging abilities for Java projects. SkyWalking: an APM(application performance monitor) system, specially designed for microservices, cloud-native and container-based (Docker and Kubernetes) architectures. -
Turn traffic into pipeline and prospects into customersDocket is an AI-powered sales enablement platform designed to unify go-to-market (GTM) data through its proprietary Sales Knowledge Lake™ and activate it with intelligent AI agents. The platform helps marketing teams increase pipeline generation by 15% by engaging website visitors in human-like conversations and qualifying leads. For sales teams, Docket improves seller efficiency by 33% by providing instant product knowledge, retrieving collateral, and creating personalized documents. Built for GTM teams, Docket integrates with over 100 tools across the revenue tech stack and offers enterprise-grade security with SOC 2 Type II, GDPR, and ISO 27001 compliance. Customers report improved win rates, shorter sales cycles, and dramatically reduced response times. Docket’s scalable, accurate, and fast AI agents deliver reliable answers with confidence scores, empowering teams to close deals faster.
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ko
Build and deploy Go applications on Kubernetes
ko is a simple, fast container image builder for Go applications. It's ideal for use cases where your image contains a single Go application without any/many dependencies on the OS base image (e.g., no cgo, no OS package dependencies). ko builds images by effectively executing go build on your local machine, and as such doesn't require docker to be installed. This can make it a good fit for lightweight CI/CD use cases. ko also includes support for simple YAML templating which makes it a... -
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KServe
Standardized Serverless ML Inference Platform on Kubernetes
KServe provides a Kubernetes Custom Resource Definition for serving machine learning (ML) models on arbitrary frameworks. It aims to solve production model serving use cases by providing performant, high abstraction interfaces for common ML frameworks like Tensorflow, XGBoost, ScikitLearn, PyTorch, and ONNX. It encapsulates the complexity of autoscaling, networking, health checking, and server configuration to bring cutting edge serving features like GPU Autoscaling, Scale to Zero, and... -
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plow
A high-performance HTTP benchmarking tool
...It can run for a set duration( option -d), for a fixed number of requests(option -n), or until Ctrl-C is interrupted. The implementation of real-time computing Histograms and Quantiles using stream-based algorithms inspired by Prometheus with low memory and CPU bounds. so it's almost no additional performance overhead for benchmarking. -
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Devtron
Tool integration platform for Kubernetes
...Provides deployment metrics like; deployment frequency, lead time, change failure rate, and mean-time recovery. Seamlessly integrates with Grafana for continuous application metrics like CPU and memory usage, status code, throughput, and latency on the dashboard. -
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The Futhark Programming Language
A data-parallel functional programming language
...It is a statically typed, data-parallel, and purely functional array language in the ML family, and comes with a heavily optimizing ahead-of-time compiler that presently generates either GPU code via CUDA and OpenCL, or multi-threaded CPU code. Futhark is not designed for graphics programming, but can instead use the compute power of the GPU to accelerate data-parallel array computations. The language supports regular nested data-parallelism, as well as a form of imperative-style in-place modification of arrays, while still preserving the purity of the language via the use of a uniqueness type system. ... -
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TensorFlow Model Garden
Models and examples built with TensorFlow
...A flexible and lightweight library that users can easily use or fork when writing customized training loop code in TensorFlow 2.x. It seamlessly integrates with tf.distribute and supports running on different device types (CPU, GPU, and TPU). -
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tvm
Open deep learning compiler stack for cpu, gpu, etc.
Apache TVM is an open source machine learning compiler framework for CPUs, GPUs, and machine learning accelerators. It aims to enable machine learning engineers to optimize and run computations efficiently on any hardware backend. The vision of the Apache TVM Project is to host a diverse community of experts and practitioners in machine learning, compilers, and systems architecture to build an accessible, extensible, and automated open-source framework that optimizes current and emerging... -
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Hasktorch
Tensors and neural networks in Haskell
Hasktorch is a powerful Haskell library for tensor computation and neural network modeling, built on top of libtorch (the backend of PyTorch). It brings differentiable programming, automatic differentiation, and efficient tensor operations into Haskell’s strongly typed functional paradigm. This project is in active development, so expect changes to the library API as it evolves. We would like to invite new users to join our Hasktorch discord space for questions and discussions.... -
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Pixie
Instant Kubernetes-Native Application Observability
...Pixie uses eBPF to automatically collect telemetry data such as full-body requests, resource and network metrics, application profiles, and more. Pixie collects, stores and queries all telemetry data locally in the cluster. Pixie uses less than 5% of cluster CPU and in most cases less than 2%. PxL, Pixie’s flexible Pythonic query language, can be used across Pixie’s UI, CLI, and client APIs. -
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Hetzner k3s
A CLI tool to install and manage Kubernetes clusters in Hetzner Cloud
...With Hetzner's Cloud Controller Manager and CSI driver you can provision load balancers and persistent volumes very easily. k3s is my favorite Kubernetes distribution now because it uses much less memory and CPU, leaving more resources to workloads. It is also super quick to deploy because it's a single binary. Using this tool, creating a highly available k3s cluster with 3 masters for the control plane and 3 worker nodes takes a few minutes only. The tool assigns the label cluster to each server it creates for static node pools (this doesn't apply to autoscaled node pools), with the cluster name you specify in the config file, as the value. -
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Ray
A unified framework for scalable computing
Modern workloads like deep learning and hyperparameter tuning are compute-intensive and require distributed or parallel execution. Ray makes it effortless to parallelize single machine code — go from a single CPU to multi-core, multi-GPU or multi-node with minimal code changes. Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. Accelerate your hyperparameter search workloads with Ray Tune. Find the best model and reduce training costs by using the latest optimization algorithms. ... -
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Amazon EC2 Instance Selector
A CLI tool and go library which recommends instance types
A CLI tool and go library which recommends instance types based on resource criteria like vcpus and memory. There are over 270 different instance types available on EC2 which can make the process of selecting appropriate instance types difficult. Instance Selector helps you select compatible instance types for your application to run on. The command-line interface can be passed resource criteria like vcpus, memory, network performance, and much more and then return the available, matching... -
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Play Framework
A high velocity web framework
...By being RESTful by default, including assets compilers, JSON & WebSocket support, Play is a perfect fit for modern web & mobile applications. Play is based on a lightweight, stateless, web-friendly architecture. Built on Akka, Play provides predictable and minimal resource consumption (CPU, memory, threads) for highly-scalable applications. Make your changes and simply hit refresh! All you need is a browser and a text editor. Underneath the covers Play uses a fully asynchronous model built on top of Akka. -
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neo.mjs
The application worker driven frontend framework
...While current libraries/frameworks like Angular, React or Vue provide reasonable performance for small or mostly static Apps, they lack when it comes to big Apps or complex Components. The problem is, that most Apps today run within a single thread (CPU), while each computer or mobile device has several CPUs available. Some Apps move expensive tasks into separate threads, but this is by far not enough. Using neo.mjs, most parts of the framework as well as the Apps which you create with it, run inside a separate thread. This architecture leaves the main thread mostly idle, so it can fully concentrate on its purpose. -
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POCO
Cross-platform C++ libraries for building network applications
The POCO C++ Libraries are powerful cross-platform C++ libraries for building network- and internet-based applications that run on desktop, server, mobile, IoT, and embedded systems. Whether building automation systems, industrial automation, IoT platforms, air traffic management systems, enterprise IT application and infrastructure management, security and network analytics, automotive infotainment and telematics, financial or healthcare, C++ developers have been trusting the POCO C++... -
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Jittor
Jittor is a high-performance deep learning framework
Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators. The whole framework and meta-operators are compiled just in time. A powerful op compiler and tuner are integrated into Jittor. It allowed us to generate high-performance code specialized for your model. Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement...
