TUHH Open Research
Help
  • Log In
    New user? Click here to register.Have you forgotten your password?
  • English
  • Deutsch
  • Communities & Collections
  • Publications
  • Research Data
  • People
  • Institutions
  • Projects
  • Statistics
  1. Home
  2. CRIS
  3. Institutions
  4. Massively Parallel Systems E-EXK5
 
  • Information
  • People
  • Publications
Options

Massively Parallel Systems E-EXK5

Director
Lal, Sohan  
Typ
TUHH Workinggroup
Website
https://www.mps.tuhh.de/
Founding Date
September 2021
Loading...
Thumbnail Image
Studiendekanat Elektrotechnik, Informatik und Mathematik (E)  
The institute of Massively Parallel Systems (MPS) investigates and teaches in the field of computer architecture, focussing on massively parallel systems.
These days massively parallel systems are present everywhere – in our smartphones, cars, supercomputers. They help us to do many things which were not possible before. For example, the recent stupendous success of machine learning, especially deep learning, is mainly due to the exponential increase in computational power. As such, machine learning is not new. Machine learning methods are around since the 1950s. What has predominately changed now is the computing power, with many-core processors such as GPUs as the main drivers. If these massively parallel processors are not utilized properly, they are very expensive in terms of power and energy consumption, which is not good as we aspire to reduce our carbon footprint. At MPS, we are working to make computing devices more performance and energy-efficient from the architecture perspective, and improve their programmability from a programmer’s perspective.
TUHH
Weiterführende Links
  • Contact
  • Send Feedback
  • Cookie settings
  • Privacy policy
  • Impress
DSpace Software

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science
Design by effective webwork GmbH

  • Deutsche NationalbibliothekDeutsche Nationalbibliothek
  • ORCiD Member OrganizationORCiD Member Organization
  • DataCiteDataCite
  • Re3DataRe3Data
  • OpenDOAROpenDOAR
  • OpenAireOpenAire
  • BASE Bielefeld Academic Search EngineBASE Bielefeld Academic Search Engine
Feedback