Search Results for "check"

...We are also introducing new TPU VMs for more transparent and easier access to the TPU hardware. This is our recommedned way of running PyTorch/XLA on Cloud TPU. Please check out our Cloud TPU VM User Guide. Cloud TPU VM is currently on general availability and provides direct access to the TPU host. The recommended setup for running distributed training on TPU Pods uses the pairing of Compute VM Instance Groups and TPU Pods. Each of the Compute VM in the instance group drives 8 cores on the TPU Pod.

2025-05-08 ====================== PLEASE NOTE ======================= Due to changes to the API of the hathirtust homepage, the HDH is no longer functional!! Please check the project Wiki for alternative methods. https://sourceforge.net/p/hathidownloadhelper/alternative/ ---------------------------------------------------------------------------------------------- Hathi Download Helper was a tool for downloading public domain books from hathitrust.org. E-Mail contact: hathidownloadhelper@hotmail.com

...Smaili (2005) Comparison of Topic Identification Methods for Arabic Language, RANLP05 : Recent Advances in Natural Language Processing ,pp. 14-17, 21-23 september 2005, Borovets, Bulgary. More useful references to check: ------------------------------------------- https://sites.google.com/site/mouradabbas9/corpora

...QCV offers a 2D visualization tool, an on-line on-the-fly parameter editor, a clock tool to evaluate computation times, and a control tool to manipulate input video and sequences of images. Multiple application examples that demonstrate the main features of this framework are provided in the last release. Check it out!

This project is my engineering diploma. It's aim is to compare the efficiency of both technologies and to check where which hacks works better. What is more one of my tasks is to compare different ways of decomposing computations in parallel.

A collection of algorithms based on the topology preserving Neural Gas algorithm for density estimation/quantization/clustering/self-organized learning. I moved this project to GitHub: https://github.com/sergioroa/neuralgas

The ETHNOS environment is composed of: 1) ETHNOS-6, a dedicated distributed real-time operating system (developed as an extension to Linux), from which the overall environment takes its name, supporting different high level representation, communication, and execution requirements, 2) a dedicated network protocol designed for both the single robot and the multi-robot environment, specifically designed for noisy wireless communication, 3) an object oriented Application Programming Interface (API) based on the C++ language (and a subset based on Java), 4) a set of additional development tools (a robot simulator, a Java-applet template, etc.). Check the official website for a Reference Manual.