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Hi-EST SIGNED

Holistic Integration of Emerging Supercomputing Technologies

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Project "Hi-EST" data sheet

The following table provides information about the project.

Coordinator
BARCELONA SUPERCOMPUTING CENTER - CENTRO NACIONAL DE SUPERCOMPUTACION 

Organization address
address: Calle Jordi Girona 31
city: BARCELONA
postcode: 8034
website: www.bsc.es

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Spain [ES]
 Project website http://hiest.bsc.es
 Total cost 1˙467˙783 €
 EC max contribution 1˙467˙783 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2014-STG
 Funding Scheme ERC-STG
 Starting year 2015
 Duration (year-month-day) from 2015-05-01   to  2020-04-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    BARCELONA SUPERCOMPUTING CENTER - CENTRO NACIONAL DE SUPERCOMPUTACION ES (BARCELONA) coordinator 1˙467˙783.00

Map

 Project objective

Hi-EST aims to address a new class of placement problem, a challenge for computational sciences that consists in mapping workloads on top of hardware resources with the goal to maximise the performance of workloads and the utilization of resources. The objective of the placement problem is to perform a more efficient management of the computing infrastructure by continuously adjusting the number and type of resources allocated to each workload.

Placement, in this context, is well known for being NP-hard, and resembles the multi-dimensional knapsack problem. Heuristics have been used in the past for different domains, providing vertical solutions that cannot be generalised. When the workload mix is heterogeneous and the infrastructure hybrid, the problem becomes even more challenging. This is the problem that Hi-EST plans to address. The approach followed will build on top of four research pillars: supervised learning of the placement properties, placement algorithms for tasks, placement algorithms for data, and software defined environments for placement enforcement.

Hi-EST plans to advance research frontiers in four different areas: 1) Adaptive Learning Algorithms: by proposing the first known use of Deep Learning techniques for guiding task and data placement decisions; 2) Task Placement: by proposing the first known algorithm to map heterogeneous sets of tasks on top of systems enabled with Active Storage capabilities, and by extending unifying performance models for heterogeneous workloads to cover and unprecedented number of workload types; 3) Data Placement: by proposing the first known algorithm used to map data on top of heterogeneous sets of key/value stores connected to Active Storage technologies; and 4) Software Defined Environments (SDE): by extending SDE description languages with a still inexistent vocabulary to describe Supercomputing workloads that will be leveraged to combine data and task placement into one single decision-making process.

 Publications

year authors and title journal last update
List of publications.
2019 Shuja-Ur-Rehman Baig, Waheed Iqbal, Josep Lluis Berral, Abdelkarim Erradi, David Carrera
Adaptive Prediction Models for Data Center Resources Utilization Estimation
published pages: 1681-1693, ISSN: 1932-4537, DOI: 10.1109/tnsm.2019.2932840
IEEE Transactions on Network and Service Management 16/4 2020-01-29
2019 Shuja-ur-Rehman Baig, Waheed Iqbal, Josep Lluis Berral, Abdelkarim Erradi, David Carrera
Real-Time Data Center\'s Telemetry Reduction and Reconstruction Using Markov Chain Models
published pages: 4039-4050, ISSN: 1932-8184, DOI: 10.1109/jsyst.2019.2918430
IEEE Systems Journal 13/4 2020-01-29
2019 Alvaro Villalba, Josep Lluis Berral, David Carrera
Constant-Time Sliding Window Framework with Reduced Memory Footprint and Efficient Bulk Evictions
published pages: 486-500, ISSN: 1045-9219, DOI: 10.1109/TPDS.2018.2868960
IEEE Transactions on Parallel and Distributed Systems 30/3 2020-01-29
2019 Nicola Cadenelli, Zoran Jaks̆ić, Jordà Polo, David Carrera
Considerations in using OpenCL on GPUs and FPGAs for throughput-oriented genomics workloads
published pages: 148-159, ISSN: 0167-739X, DOI: 10.1016/j.future.2018.11.028
Future Generation Computer Systems 94 2020-01-29
2018 Juan Luis Pérez, Alberto Gutierrez-Torre, Josep Ll. Berral, David Carrera
A resilient and distributed near real-time traffic forecasting application for Fog computing environments
published pages: 198-212, ISSN: 0167-739X, DOI: 10.1016/j.future.2018.05.013
Future Generation Computer Systems 87 2019-05-29
2017 Josep Lluis Berral, Nicolas Poggi, David Carrera, Aaron Call, Rob Reinauer, Daron Green
ALOJA: A Framework for Benchmarking and Predictive Analytics in Hadoop Deployments
published pages: 480-493, ISSN: 2168-6750, DOI: 10.1109/TETC.2015.2496504
IEEE Transactions on Emerging Topics in Computing 5/4 2019-05-29
2018 David Buchaca Prats, Josep Lluis Berral, David Carrera
Automatic Generation of Workload Profiles using Unsupervised Learning Pipelines
published pages: 1-1, ISSN: 1932-4537, DOI: 10.1109/TNSM.2017.2786047
IEEE Transactions on Network and Service Management 4 2019-05-27

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