Search Results for "hardware"

Covalent is a Pythonic workflow tool for computational scientists, AI/ML software engineers, and anyone who needs to run experiments on limited or expensive computing resources including quantum computers, HPC clusters, GPU arrays, and cloud services. Covalent enables a researcher to run computation tasks on an advanced hardware platform – such as a quantum computer or serverless HPC cluster – using a single line of code. Covalent overcomes computational and operational challenges inherent in AI/ML experimentation.

...Unlike other distributed DataFrame libraries, Modin provides seamless integration and compatibility with existing pandas code. Even using the DataFrame constructor is identical. It is not necessary to know in advance the available hardware resources in order to use Modin. Additionally, it is not necessary to specify how to distribute or place data. Modin acts as a drop-in replacement for pandas, which means that you can continue using your previous pandas notebooks, unchanged, while experiencing a considerable speedup thanks to Modin, even on a single machine. Once you’ve changed your import statement, you’re ready to use Modin just like you would pandas.

This project delivers Linux support (USB driver and Tools) for a Digital Signal Processor (DSP) cards of the Signal Ranger series, see http://www.softdb.com/product_dsp.shtml for details) connected to a Linux host via USB.

GXSM -- Gnome X Scanning Microscopy: A multi-channel image and vector-probe data acquisition and visualization system designed for SPM techniques (STM,AFM..), but also SPA-LEED/LEED/LEEM data analysis. A plug-in interface allows any user add-on data-processing and special hardware and instrument support. Latest: NC-AFM and related explorative methods as SQDM can be configured. High-Speed external PAC-PLL hardware option with digital DSP link. Based on several hardware options it supports a commercially available DSP hardware and provided also Open Source Code for all the low level signal processing tasks and instrument controls in a most flexible and adaptable manner. ...

All-in-one web-based development environment for machine learning. The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on your own machines. This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard)...

...We provide a model collection to help you find some popular models. We provide a model visualizer to display the network architecture more intuitively. We provide some guidelines to help you deploy DL models to another hardware platform.

This tool generates timing diagrams for documenting hardware design. It reads the description from a text file with a simple syntax. It generates vector graphic (EPS, SVG or EMF format). It can be used in command line mode or with a GUI. It is written in Python and works on any platform.

TotalDepth is an Open Source, cross platform, software collection that can process petrophysical data from the oil field such as wireline logs, seismic data and so on. Conventional, proprietary, software for petrophysical data tends to be expensive to licence, restrictive, slow to develop for and tied to expensive hardware. TotalDepth changes all of that. TotalDepth is open and cross-platform, and produces results straight to the bowser. TotalDepth supports such technologies such as HTML5, AJAX, Software as a Service (SaaS) and Cloud Computing.

Retrieve statistics from SNMP-aware devices, store them in a database and graphically display them for monitoring and notification purposes.