DSATS : Research and Project

Category: Miscellaneous    

Date Listed/Updated: 2023-01-29 01:48:57

File size: 1012 KB

OS: WinXP,Win7 x32,Win7 x64,Windows 8,Windows 10,Windows2003,Windows Server 2003,Windows Server 2008,Windows Server 2008r2,Windows Server 2012,Windows Tablet PC Edition 2005,Windows Media Center Edition 2005,WinVista,Windows Vista Starter,Windows Vista Home Basic,Windows Vista Home Premium,Windows Vista Business,Windows Vista Enterprise,Windows Vista Ultimate,WinVista x64,Windows Vista Home Basic x64,Windows Vista Home Premium x64,Windows Vista Business x64,Windows Vista Enterprise x64,Windows Vista  License: Other  Price($): 0

Author/Publisher name: DSATS DSATS

  View Full Screenshot

Description:

DSATS : Research & Project Architecture and Structure Aware Linear Algebra Linear algebra (LA) operations are fundamental to a large number of computational science algorithms. LA algorithms is complicated by the increasing architectural heterogeneity of the high-performance computing (HPC) platforms. This project aims to build an Architecture and Data-Structure Aware Linear Algebra (ADSALA) software package that will use machine learning to learn the hardware data-structure package algorithm relationships when compiled on a specific hardware architecture for a spectrum of LA packages. DSATS : Research & Project The pursuit of optimal LA algorithms is significantly complicated by the increasing architectural heterogeneity of the high-performance computing (HPC) platforms, with a variable mix of general-purpose processors (CPUs) and accelerators (GPUs, DSPs, FPGAs, etc.), and complex associated memory hierarchies and file systems. DSATS : Research & Project Linear algebra (LA) operations are fundamental to a large number of computational science algorithms. The applications span the entire scientific board, with machine learning (ML) algorithms being among the most reliant on LA operations; they provide the mathematics that underpins much of what we do. Historically, this fact has driven the development of a plethora of libraries providing high-performance implementations of LA algorithms: BLAS, OpenBLAS, cuBLAS, CLBLAS, LAPACK, ARPACK, ATLAS, cuSOLVER, MAGMA and many more. For a given LA operation, the choice can be bewildering for the programmer, especially given that within the same library there may be several algorithms yielding different performance depending, for example, on the specific structure of the matrices involved.

EULA

Tags: DSATS Project  DSATS LeaderShip  DSATS TEAM  TEAM  Leadership DSATS   

Is this software spam? Report Spam

Software removal request by publisher Removal Request

Software Review: DSATS : Research and Project Review

For publisher: Request Software Confirmation

DSATS releases the fastest High Performance Computing (HPC) machines for testing of algorithms in India.< b> State of the art high performance computing centre is pro bono for non-profits and universities and provides an onshore vulnerability analysis centre.< i>
New Delhi, India: DSATS< b> has established a High Performance Computing (HPC) lab in India that enables an organisation to test the security of their encrypted data. The HPC lab is available for Indian customers to protect data security and safety as the lab is located within shores.
The project consists of expandable components that include AI based customised Crypt Analysis Software Platform with added modules, tools based on Artificial Intelligence and Neural Networks and High-Performance Super Computer Hardware System with Complete Storage, Cooling, Racking, Power Backup.
Ankur Srivastava< b> commented that while several providers are enabling such services the lab is present in India and is fully compliant to existing privacy and data protection laws of the country. The lab also provides HaaS (Hardware as a Service) by means of co-location, onsite setup and online access to test sensitive data. This service has been released to all government recognised universities at pro-bono.

This lab targeted specifically for universities in India don t need a registered account. A university can use the free tiered account to get 1,000 GB of free data transfer each month or upload unto 50 PCAP files each with a maximum size of 250 GB. The PCAP data is removed after analysis including meta data to ensure privacy of user data. The universities can also visit the HPC lab and upload the data manually for advanced analysis. This free tiered data may be upgraded at a price of INR 10,000 per year for unlimited analysis.

Visit the Press Release for more details