Showing 5 open source projects for "wise memory optimizer"

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  • 1
    Polars

    Polars

    Dataframes powered by a multithreaded, vectorized query engine

    Polars is a high-performance, multi-language DataFrame library built in Rust using Apache Arrow. It delivers blazing-fast, vectorized, and parallel data manipulation with both eager and lazy execution, making it an excellent tool for data processing in Python, Rust, Node.js, R, and SQL contexts.
    Downloads: 0 This Week
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  • 2
    TensorRT

    TensorRT

    C++ library for high performance inference on NVIDIA GPUs

    NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference. It includes a deep learning inference optimizer and runtime that delivers low latency and high throughput for deep learning inference applications. TensorRT-based applications perform up to 40X faster than CPU-only platforms during inference. With TensorRT, you can optimize neural network models trained in all major frameworks, calibrate for lower precision with high accuracy, and deploy to hyperscale data centers,...
    Downloads: 30 This Week
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  • 3
    FairScale

    FairScale

    PyTorch extensions for high performance and large scale training

    FairScale is a collection of PyTorch performance and scaling primitives that pioneered many of the ideas now used for large-model training. It introduced Fully Sharded Data Parallel (FSDP) style techniques that shard model parameters, gradients, and optimizer states across ranks to fit bigger models into the same memory budget. The library also provides pipeline parallelism, activation checkpointing, mixed precision, optimizer state sharding (OSS), and auto-wrapping policies that reduce boilerplate in complex distributed setups. Its components are modular, so teams can adopt just the sharding optimizer or the pipeline engine without rewriting their training loop. ...
    Downloads: 0 This Week
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  • 4
    Fairseq

    Fairseq

    Facebook AI Research Sequence-to-Sequence Toolkit written in Python

    Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the...
    Downloads: 0 This Week
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  • 5

    JILRuntime/JewelScript

    An object-oriented script language to embed in any application

    A general purpose, object-oriented script language that compiles into code for a register based virtual machine. The language is quite similar to object-oriented high-level languages like Java and C#. The library is entirely self-sufficient and ANSI C compliant. It's main purpose is to be embedded in any application to allow automation of that application through scripting. An integrated C++ binding code generator allows you to create bindings for your application's classes in seconds....
    Downloads: 0 This Week
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