Search Results for "bandwidth"

...Because MoE architectures require routing inputs to different experts, communication overhead can become a bottleneck — DeepEP addresses that by providing optimized GPU kernels and efficient dispatch/combining logic. The library also supports low-precision operations (such as FP8) to reduce memory and bandwidth usage during communication. DeepEP is aimed at large-scale model inference or training systems where expert parallelism is used to scale model capacity without replicating entire networks.

Intel CMT CAT is a user-space software package providing support for Intel's Resource Director Technology (RDT). It offers tools and libraries to monitor and control cache allocation and memory bandwidth.​

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,...

...For users, this means apps can now be downloaded faster, 3D graphics in the browser can load quicker, and VR and AR scenes can now be transmitted with a fraction of the bandwidth and rendered quickly.

...The RAPIDS suite of open-source software libraries aims to enable the execution of end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization but exposing that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces.

JavaScript-Load-Image is a client-side image loading and processing library that focuses on turning File/Blob objects or remote URLs into HTML <img> or <canvas> elements, optionally transformed in the process. It is often used in upload flows where images need to be previewed, resized, rotated, or cropped before being sent to a server, reducing bandwidth and improving user experience. The library can interpret image metadata, including Exif and IPTC tags, and can extract embedded thumbnails when present, which is handy for building fast image pickers or galleries. One of its key capabilities is correcting Exif Orientation, so photos taken on mobile devices appear upright without additional server-side processing. ...

...Out of the box it supports JSON, string, and image requests, plus an extensible Request/Response model for custom payloads. Volley emphasizes responsiveness: transparent caching and de-duplication of in-flight requests help reduce latency and bandwidth usage. Error handling, retries with backoff, and request prioritization are first-class, making it easier to handle flaky mobile networks. While Android has other HTTP stacks, Volley’s value is in opinionated, high-level primitives that fit common app patterns without pulling in heavy dependencies.

This project contains a collection of RMI socket factories -- for instance gzip-encoded data sent over the wire, NIO-based communication etc.