Search Results for "wise memory optimizer"
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Showing 8 open source projects for "wise memory optimizer"
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rtabmap
RTAB-Map library and standalone application
...The loop closure detector uses a bag-of-words approach to determine how likely a new image comes from a previous location or a new location. When a loop closure hypothesis is accepted, a new constraint is added to the map’s graph, then a graph optimizer minimizes the errors in the map. A memory management approach is used to limit the number of locations used for loop closure detection and graph optimization so that real-time constraints on large-scale environments are always respected. RTAB-Map can be used alone with a handheld Kinect, a stereo camera or a 3D lidar for 6DoF mapping, or on a robot equipped with a laser rangefinder for 3DoF mapping. -
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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. -
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PhoneNumberKit
A Swift framework for parsing and formatting phone numbers
...All of your interactions with PhoneNumberKit happen through a PhoneNumberKit object. The first step you should take is to allocate one. A PhoneNumberKit instance is relatively expensive to allocate (it parses the metadata and keeps it in memory for the object's lifecycle), you should try and make sure PhoneNumberKit is allocated once and deallocated when no longer needed. To parse a string, use the parse function. The region code is automatically computed but can be overridden if needed. PhoneNumberKit automatically does a hard type validation to ensure that the object created is valid, this can be quite costly performance-wise and can be turned off if needed. -
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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,... -
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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. ... -
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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... -
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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.... -
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Drawable Optimizer
Gradle plugin to optimize png files and reduce resultant apk size
...Developers can fine-tune which directories and formats to process and exclude sensitive assets where bit-exactness matters. The result is faster downloads, lower install sizes, and improved memory characteristics on resource-constrained devices. It fits naturally into continuous integration, ensuring optimizations remain consistent over time.
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