Grant: Alliance Grants
École Polytechnique de Montréal
$342,860.00
Tuning, Debugging and Monitoring High Performance Heterogeneous Systems at Exascale
EF 2024-25
Résumé
In recent years, the computing infrastructure continued its rapid development with increased computing capacity and bandwidth, increased connectivity, and the widespread use of special purpose heterogeneous processors for specific tasks. These very large scale computing systems are being used for networking and telecommunications, for data centers, and for scientific computing. The term Exascale (10^18 operations per second) illustrates well the current state of the art and the challenge of getting so many computations, from millions of cores, combined together in a single application. The complexity at the hardware level comes from the very large number of concurrent nodes running asynchronously, the hardware heterogeneity, and the networking sophistication. The complexity at the software level comes from the distribution of the computation over several networked nodes that may fail, and the large number of software layers.
In order to monitor, diagnose and solve problems in such systems, especially performance problems, it is necessary to have full observability through all layers through tracing, to link together the information gathered in each layer, and to provide high level trace analysis and debugging tools. Those tools will help analyse and visualise the resulting information. This is the primary objective of the proposed project which is structured along 4 tracks: Runtime Tracing, Debugging and Verification; Heterogeneous and High Performance Computing; Distributed Cloud Applications and Integrated Development Environments; and Automating System Monitoring and Anomaly detection. This project develops enabling technologies to increase the efficiency of the Canadian ICT sector. It will help to increase the performance and reduce the development time of new products. It will further the Canadian industrial strength in this high-value technology sector, at a time when Cloud Computing, Exascale Supercomputers, Heterogeneous Systems and Machine Learning are at the forefront of the high technology sector.
Programme
Alliance Grants
Bénéficiaire
Emplacement
Quebec, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
586658-2023
Name nom
Dagenais, Michel MR
Department département
Génie informatique et génie logiciel
Organization id
64
Institution établissement
École Polytechnique de Montréal
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2023
Award amount
342860
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
1207
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Information, computer and communication technologies
Area of application fr
Technologie de l'information, des ordinateurs et des réseaux de communications
Research subject code
2720
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Computer systems software
Research subject fr
Logiciel de systèmes informatiques
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Tuning, Debugging and Monitoring High Performance Heterogeneous Systems at Exascale
Keywords
cloud computing; debugging; exascale computing; gpgpu; heterogeneous computer systems; high performance computing; integrated development environment; machine learning; profiling; tracing
Application summary
In recent years, the computing infrastructure continued its rapid development with increased computing capacity and bandwidth, increased connectivity, and the widespread use of special purpose heterogeneous processors for specific tasks. These very large scale computing systems are being used for networking and telecommunications, for data centers, and for scientific computing. The term Exascale (10^18 operations per second) illustrates well the current state of the art and the challenge of getting so many computations, from millions of cores, combined together in a single application. The complexity at the hardware level comes from the very large number of concurrent nodes running asynchronously, the hardware heterogeneity, and the networking sophistication. The complexity at the software level comes from the distribution of the computation over several networked nodes that may fail, and the large number of software layers.
In order to monitor, diagnose and solve problems in such systems, especially performance problems, it is necessary to have full observability through all layers through tracing, to link together the information gathered in each layer, and to provide high level trace analysis and debugging tools. Those tools will help analyse and visualise the resulting information. This is the primary objective of the proposed project which is structured along 4 tracks: Runtime Tracing, Debugging and Verification; Heterogeneous and High Performance Computing; Distributed Cloud Applications and Integrated Development Environments; and Automating System Monitoring and Anomaly detection. This project develops enabling technologies to increase the efficiency of the Canadian ICT sector. It will help to increase the performance and reduce the development time of new products. It will further the Canadian industrial strength in this high-value technology sector, at a time when Cloud Computing, Exascale Supercomputers, Heterogeneous Systems and Machine Learning are at the forefront of the high technology sector.
