Showing 5 open source projects for "cpu"

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  • Train ML Models With SQL You Already Know Icon
    Train ML Models With SQL You Already Know

    BigQuery automates data prep, analysis, and predictions with built-in AI assistance.

    Build and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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  • 1
    R3nzSkin

    R3nzSkin

    Skin changer for League of Legends (LOL)

    R3nzSkin is an internal skin changer for League of Legends. Change the skin of your champion, your ward, other champions, towers, minions, and jungle monsters in the game. If your CPU supports the AVX / AVX2 / AVX-512 instruction set, you can enable it in project settings. This should result in more performant code, optimized for your CPU. Currently, SSE2 instructions are selected in project settings. Change skins anytime and unlimited times in a single game. Supports all popular languages ​​in the world.
    Downloads: 29 This Week
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  • 2
    simdjson

    simdjson

    Parsing gigabytes of JSON per second

    JSON is everywhere on the Internet. Servers spend a *lot* of time parsing it. We need a fresh approach. The simdjson library uses commonly available SIMD instructions and microparallel algorithms to parse JSON 4x faster than RapidJSON and 25x faster than JSON for Modern C++. The simdjson library uses three-quarters less instructions than state-of-the-art parser RapidJSON. To our knowledge, simdjson is the first fully-validating JSON parser to run at gigabytes per second (GB/s) on commodity...
    Downloads: 0 This Week
    Last Update:
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  • 3
    DocArray

    DocArray

    The data structure for multimodal data

    ...Data science powerhouse: greatly accelerate data scientists’ work on embedding, k-NN matching, querying, visualizing, evaluating via Torch/TensorFlow/ONNX/PaddlePaddle on CPU/GPU. Data in transit: optimized for network communication, ready-to-wire at anytime with fast and compressed serialization in Protobuf, bytes, base64, JSON, CSV, DataFrame. Perfect for streaming and out-of-memory data. One-stop k-NN: Unified and consistent API for mainstream vector databases.
    Downloads: 0 This Week
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  • 4

    Occursions

    Fast customizable time series web database for big data like log files

    ...Occursions asynchronously tails log files and indexes the individual lines in each log file as each line is written to disk so you don't even have to wait for a second after an event happens to search for it. Occursions uses custom disk backed data structures to create and search its indexes so it is very efficient at using CPU, memory and disk. You can extend Occursions with shared libraries to support your own file formats, even binary file formats!
    Downloads: 0 This Week
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  • Custom VMs From 1 to 96 vCPUs With 99.95% Uptime Icon
    Custom VMs From 1 to 96 vCPUs With 99.95% Uptime

    General-purpose, compute-optimized, or GPU/TPU-accelerated. Built to your exact specs.

    Live migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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  • 5
    Tpl makes it easy to serialize your C data using just a handful of API functions. The data is stored in its native binary form for maximum efficiency. C, Perl and XML supported. Data is portable across CPU types and OS's from Unix to Mac to Windows.
    Downloads: 0 This Week
    Last Update:
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