Search Results for "android-x86_32"
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Showing 3 open source projects for "android-x86_32"
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AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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Atera all-in-one platform IT management software with AI agentsAtera’s AI agents don’t just assist, they act. From detection to resolution, they handle incidents and requests instantly, taking your IT management from automated to autonomous.
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plow
A high-performance HTTP benchmarking tool
Plow is an HTTP(S) benchmarking tool, written in Golang. It uses excellent fast HTTP instead of Go's default net/http due to its lightning-fast performance. Plow runs at specified connections (option -c) concurrently and real-time records summary statistics, histogram of execution time and calculates percentiles to display on Web UI and terminal. 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... -
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In 2015, we converted cBench to open Collective Knowledge Format (CK) and moved it here: http://github.com/ctuning/ctuning-programs CK allows you to simplify compilation and execution of these benchmarks across multiple platforms (Windows, Linux, MacOS, Android ...). Collective Benchmark (cBench) is a collection/extension of open-source programs and multiple datasets to enable realistic benchmarking and research on program and architecture optimization.
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In 2015, we converted MiDataSets and cDataSets to open Collective Knowledge Format (CK) and moved them here: http://github.com/ctuning/ctuning-datasets-min CK allows you to simplify compilation and execution of these benchmarks across multiple platforms (Windows, Linux, MacOS, Android ...). In this project, we collect multiple datasets for a MiBench benchmark (free, commercially representative embedded benchmark suite) to create the conditions for a more realistic benchmarking of different computing systems.
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