Search Results for "cpu benchmark linux"
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24 projects for "cpu benchmark linux" with 2 filters applied:
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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BenchmarkTools.jl
A benchmarking framework for the Julia language
BenchmarkTools makes performance tracking of Julia code easy by supplying a framework for writing and running groups of benchmarks as well as comparing benchmark results. This package is used to write and run the benchmarks found in BaseBenchmarks.jl. The CI infrastructure for automated performance testing of the Julia language is not in this package but can be found in Nanosoldier.jl. Our story begins with two packages, "Benchmarks" and "BenchmarkTrackers". The Benchmarks package... -
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SIA
AI framework to autonomously improve the performance of any AI system
SIA is a self-improving AI framework designed to improve the performance of models or agents on benchmark tasks. It uses an iterative loop where a meta-agent creates or updates a task-specific target agent, while a feedback agent studies results and proposes improvements. The framework can refine both the harness around the task and the agent implementation itself. It is aimed at research and experimentation across tasks such as machine learning benchmarks, legal classification, code... -
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Piscina
A fast, efficient Node.js Worker Thread Pool implementation
Piscina is a fast, efficient Node.js worker thread pool implementation, designed to perform heavy CPU-bound tasks in parallel, thereby improving application performance. -
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Apache Sedona
Cluster computing framework for processing large-scale geospatial data
Apache Sedona™ is a cluster computing system for processing large-scale spatial data. Sedona extends existing cluster computing systems, such as Apache Spark and Apache Flink, with a set of out-of-the-box distributed Spatial Datasets and Spatial SQL that efficiently load, process, and analyze large-scale spatial data across machines. According to our benchmark and third-party research papers, Sedona runs 2X - 10X faster than other Spark-based geospatial data systems on computation-intensive... -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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Phalcon
High performance, full-stack PHP framework delivered as a C extension
Its innovative architecture makes Phalcon the fastest PHP framework ever built! Developers do not need to know C to use Phalcon. Its functionality is exposed as PHP classes and interfaces under the Phalcon namespace, ready to be used. Zephir/C extensions are loaded together with PHP one time on the web server's daemon start process. Classes and functions provided by the extension are ready to use for any application. The code is compiled and isn't interpreted because it's already compiled to... -
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SDWebImageSwiftUI
SwiftUI Image loading and Animation framework powered by SDWebImage
SDWebImageSwiftUI is a SwiftUI image-loading framework, which is based on SDWebImage. It brings all your favorite features from SDWebImage, like async image loading, memory/disk caching, animated image playback and performances. The framework provide the different View structs, which API match the SwiftUI framework guideline. If you're familiar with Image, you'll find it easy to use WebImage and AnimatedImage. Since SDWebImageSwiftUI is built on top of SDWebImage, it provide both the... -
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Chipyard
An Agile RISC-V SoC Design Framework with in-order cores
Chipyard is a framework and generator for constructing custom RISC‑V SoC hardware. Built at UC Berkeley, it leverages Chisel/FIRRTL to generate full-stack systems—from CPU cores to peripherals—and includes simulators, FPGA deployment tools, and integration with Rocket Chip and other RISC‑V ecosystems. -
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bitnet.cpp
Official inference framework for 1-bit LLMs
bitnet.cpp is the official open-source inference framework and ecosystem designed to enable ultra-efficient execution of 1-bit large language models (LLMs), which quantize most model parameters to ternary values (-1, 0, +1) while maintaining competitive performance with full-precision counterparts. At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous... -
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Axe
Logger-agnostic wrapper that normalizes logs regardless of arg style
Logger-agnostic wrapper that normalizes logs regardless of arg style. Great for large dev teams, old/new projects, and works w/Pino, Bunyan, Winston, console, and more. It is lightweight, performant, highly-configurable, and automatically adds OS, CPU, and Git information to your logs. Hooks, dot-notation remap, omit, and pick of metadata. Axe was built to provide consistency among development teams when it comes to logging. You not only have to worry about your development team using the... -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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TorchQuantum
A PyTorch-based framework for Quantum Classical Simulation
A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers. Researchers on quantum algorithm design, parameterized quantum circuit training, quantum optimal control, quantum machine learning, and quantum neural networks. Dynamic computation graph, automatic gradient computation, fast GPU support, batch model terrorized processing. -
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MetalPetal
A GPU accelerated image and video processing framework built on Metal
MetalPetal is an image processing framework based on Metal designed to provide real-time processing for still images and video with easy-to-use programming interfaces. This chapter covers the key concepts of MetalPetal, and will help you to get a better understanding of its design, implementation, performance implications, and best practices. A MTIImage object is a representation of an image to be processed or produced. It does directly represent image bitmap data instead it has all the... -
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Mocha.jl
Deep Learning framework for Julia
Mocha.jl is a deep learning framework for Julia, inspired by the C++ Caffe framework. It offers efficient implementations of gradient descent solvers and common neural network layers, supports optional unsupervised pre-training, and allows switching to a GPU backend for accelerated performance. The development of Mocha.jl happens in relative early days of Julia. Now that both Julia and the ecosystem has evolved significantly, and with some exciting new tech such as writing GPU kernels... -
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A parallel-programming framework for concurrently running large numbers of small autonomous jobs, or microthreads, across multiple cores in a CPU or CPUs in a cluster. Each microthread is conceptually similar to a task in Ada and it is much lighter weight than an operating system thread. SpikeOS was designed to handle millions of microthreads, for example in a neural network hosting millions of spiking model neurons. SpikeOS handles microthread scheduling, synchronization, distribution...
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TRMSim-WSN (Trust and Reputation Models Simulator for Wireless Sensor Networks) is a Java-based simulator aimed to test Trust and Reputation models for WSNs. It provides several Trust and Reputation models and new ones can be easily added.
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MongoLantern - MongoDB Fulltext Search
Open Source MongoDB Fulltext Search Server
MongoLantern is an open source full text search server using MongoDB as index storage, which allows MongoLantern to migrate any changes very easily into account using MongoDB API. It's written originally written in PHP can be migrated to any desired language as required using it's future APIs. MongoLantern 0.7 - Stable/Production Release: 1. MongoLantern API support enabled. 2. CSV indexer added as a plugin. 3. node.js API client added. -
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A fully automated database benchmark suite that prints tabular and graphic results for multiple tested disciplines, given JDBC database connections. Some free open source database engines are included.
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IMPORTANT: This project is no longer maintained. All the effort is targeted on project Radargun: http://radargun.sourceforge.net
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A light-weight cross platform C++ library for console and file I/O, fast data structures and algorithms, CPU identification (CPUID), and sockets (TCP and UDP).
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An open source framework for unit test and performance benchmark, initiated by Andrew Zhang. p-unit supports to run the same tests with single thread or multi-threads, tracks memory and time consumption, and generates the result as pdf/jpg/png/txt file.
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This is a small C-library to create an maintain the tray icons in your own programs and a set of tiny lightning-fast trayicon utilities to show the cpu-load, mem-load, xkb-layout & mixer-volumes.
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AdaptiveCells J2EE generates test-beds for benchmarking J2EE performance. They consists of highly customizable EJB cells that can emulate CPU load, memory usage, memory leaks and exceptions. The behaviour of the cells is coordinated from a web front-end.
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Project aims to simplify Linux kernel analysis and development. Primary audience to the result of project will be (under)graduate students attending "Operating system" courses. It is our intention to make advances with every generation of students.
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A generic java based distributed performance testing platform specifically for testing clustered or distributed applications and or frameworks. The framework itself is clustered and coordinated with www.terracotta.org
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