Due to fundamental limitations of scaling at the atomic scale, coupled with the heat density problems associated with packing an ever-increasing number of transistors in a unit area, Moore's Law has slowed down. Heterogeneity aims to solve the problems associated with the end of Moores Law by incorporating more specialized compute units in the system hardware and by utilizing the most efficient compute unit for each computation. However, while in the last years a lot of research and advances were made to support heterogeneity for performance; for power- and energy-efficient computing it is severely lacking.
The overall objective of the LEGaTO project is to produce a mature software stack to optimize the energy-efficiency heterogeneous computing. The project will strive to achieve this objective through employing a task-based programming model, coupled to a dataflow runtime while simultaneously ensuring security, resilience and programmability. The LEGaTO project will apply this energy-efficient software stack for heterogeneous hardware to the use cases of health care, smart home/city and machine learning.
Concrete targets of the LEGATO project are:
Osman Unsal and Adrian Cristal, coordinators of LEGaTO project and BSCs Computer Architecture for Parallel Paradigms group managers, stated: "Moore's Law is slowing down, and as a consequence hardware is becoming more heterogeneous. In the LEGaTO project, we will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. Our aim is one order of magnitude energy savings from the edge to the converged cloud/HPC."
The LEGaTO project is funded by the European Commission with a budget of more than 5 million euro and will last 3 years from its beginning on 1 December 2017. The partners of the project are Barcelona Supercomputing Center (BSC, Spain), Universitaet Bielefeld (UNIBI, Germany), Universite de Neuchatel (UNINE, Switzerland), Chalmers Tekniska Hoegskola AB (CHALMERS, Sweden), Data Intelligence Sweden AB (DIS, Sweden), Technische Universität Dresden (TUD, Germany), Christmann Informationstechnik + Medien GmbH & Co. KG (CHR, Germany), Helmholtz-Zentrum für Infektionsforschung GmbH (HZI, Germany), TECHNION - Israel Institute of Technology (TECHNION, Israel), and Maxeler Technologies Limited (MAXELER, United Kingdom).