Periodic Reporting for period 1 - SPACE (Scalable Parallel and distributed Astrophysical Codes for Exascale)
Período documentado: 2023-01-01 hasta 2023-12-31
In Astrophysics and Cosmology (A&C) today, High Performance Computing (HPC)-based numerical simulations are outstanding instruments for scientific discovery.
They represent essential tools and theoretical laboratories able to investigate, interpret and understand the physical processes behind the observed sky.
For these laboratories, the efficient and effective exploitation of exascale computing capabilities is essential.
Exascale systems, however, are expected to have a heterogeneous unprecedented architectural complexity, with a significant impact on simulation codes.
Consequently, the Scalable Parallel Astrophysical Codes for Exascale (SPACE) Centre of Excellence (CoE) is aiming at extensively re-engineer seven target codes (Open GADGET, CHANGA/GASOLINE, PLUTO, iPic3D, RAMSES, FIL, and BHAC) to engage with new computational solutions and adopt innovative programming paradigms, software solutions, and libraries. Also, SPACE is fostering the reuse and sharing of algorithms and software components in the A&C application domain.
The SPACE CoE is addressing HORIZON-EUROHPC-JU-2021-COE-01 action through co-design activities that bring together scientists, code developers, HPC experts, HW manufacturers and SW developers, advancing seven lighthouse exascale A&C applications, codes, services and know-how promoting the use of upcoming exascale and post-exascale computing capabilities.
In addition, SPACE is addressing the high-performance data analysis of the data torrent produced by exascale A&C simulation applications, also with machine-learning and visualization tools.
The deployment of applications running on different platforms is being facilitated by federating capabilities focusing on code repositories and data sharing, and integrating European astrophysical communities around exascale computing by adopting software and data standards and interoperability protocols.
Therefore, SPACE CoE is promoting and supporting cutting-edge science through effective exploitation of exascale resources, by:
1. anticipating the challenges of the exascale era, focusing on applications and algorithms re-engineering and development leveraging a co-design working methodology, enhancing and characterizing their energy efficiency;
2. adopting standardized and interoperable solutions for software and FAIR principles have the intent to act as a guideline for those wishing to enhance the reusability of their data holdings and put specific emphasis on enhancing the ability of machines to automatically find and use the data (FAIR principles) for data;
3. promoting the related know-how within the community and beyond, i.e industrial applications or related scientific domains such as plasma physics or Computational fluid dynamics (CFD). This allows to extend the user base and enable an increasing number of researchers to effectively use and adopt advanced HPC solutions.
During this period, SPACE managed to address several actions toward achieving its objectives; managed to broadly disseminate, communicate, as well as shape effectively the preliminary exploitation of the seven lighthouse exascale A&C applications; managed to establish fruitful collaborations, innovation activities, undertake synergies and collaboration with complementary grants and CASTIEL2 including user-engagement, thus strengthening and securing the overall project’s impact.
They represent essential tools and theoretical laboratories able to investigate, interpret and understand the physical processes behind the observed sky.
For these laboratories, the efficient and effective exploitation of exascale computing capabilities is essential.
Exascale systems, however, are expected to have a heterogeneous unprecedented architectural complexity, with a significant impact on simulation codes.
Consequently, the Scalable Parallel Astrophysical Codes for Exascale (SPACE) Centre of Excellence (CoE) is aiming at extensively re-engineer seven target codes (Open GADGET, CHANGA/GASOLINE, PLUTO, iPic3D, RAMSES, FIL, and BHAC) to engage with new computational solutions and adopt innovative programming paradigms, software solutions, and libraries. Also, SPACE is fostering the reuse and sharing of algorithms and software components in the A&C application domain.
The SPACE CoE is addressing HORIZON-EUROHPC-JU-2021-COE-01 action through co-design activities that bring together scientists, code developers, HPC experts, HW manufacturers and SW developers, advancing seven lighthouse exascale A&C applications, codes, services and know-how promoting the use of upcoming exascale and post-exascale computing capabilities.
In addition, SPACE is addressing the high-performance data analysis of the data torrent produced by exascale A&C simulation applications, also with machine-learning and visualization tools.
The deployment of applications running on different platforms is being facilitated by federating capabilities focusing on code repositories and data sharing, and integrating European astrophysical communities around exascale computing by adopting software and data standards and interoperability protocols.
Therefore, SPACE CoE is promoting and supporting cutting-edge science through effective exploitation of exascale resources, by:
1. anticipating the challenges of the exascale era, focusing on applications and algorithms re-engineering and development leveraging a co-design working methodology, enhancing and characterizing their energy efficiency;
2. adopting standardized and interoperable solutions for software and FAIR principles have the intent to act as a guideline for those wishing to enhance the reusability of their data holdings and put specific emphasis on enhancing the ability of machines to automatically find and use the data (FAIR principles) for data;
3. promoting the related know-how within the community and beyond, i.e industrial applications or related scientific domains such as plasma physics or Computational fluid dynamics (CFD). This allows to extend the user base and enable an increasing number of researchers to effectively use and adopt advanced HPC solutions.
During this period, SPACE managed to address several actions toward achieving its objectives; managed to broadly disseminate, communicate, as well as shape effectively the preliminary exploitation of the seven lighthouse exascale A&C applications; managed to establish fruitful collaborations, innovation activities, undertake synergies and collaboration with complementary grants and CASTIEL2 including user-engagement, thus strengthening and securing the overall project’s impact.
The CoE’s objective are explicitly declared in the Grant Agreement. We recap them here by adding, for each
one, the achievements reached during the first year of activity.
• [Objective 1] Enabling of SPACE codes to exascale and extreme scaling performance by
adopting a co-design methodology in order to address cutting-edge scientific, industrial, or
societal challenges (WP1, WP2, WP4).
• [Objective 2] Advancing the exascale readiness of existing and already productive post-processing codes,
enhancing the integration of existing pipelines (WP1, WP3).
• [Objective 3]
Integrating advanced AI and ML techniques to post-processing and data-mining, exploring
the coupling of AI and ML “solvers” four run-time coupling with computational codes (WP1,
WP3).
• [Objective 4] Addressing the Energy Efficiency.
• [Objective 5] Building, Organizing and Federating the A&C community, widening access to codes and ad-
vanced computing services, fostering the transfer of know-how to user communities. (WP1,
WP2, WP3)
one, the achievements reached during the first year of activity.
• [Objective 1] Enabling of SPACE codes to exascale and extreme scaling performance by
adopting a co-design methodology in order to address cutting-edge scientific, industrial, or
societal challenges (WP1, WP2, WP4).
• [Objective 2] Advancing the exascale readiness of existing and already productive post-processing codes,
enhancing the integration of existing pipelines (WP1, WP3).
• [Objective 3]
Integrating advanced AI and ML techniques to post-processing and data-mining, exploring
the coupling of AI and ML “solvers” four run-time coupling with computational codes (WP1,
WP3).
• [Objective 4] Addressing the Energy Efficiency.
• [Objective 5] Building, Organizing and Federating the A&C community, widening access to codes and ad-
vanced computing services, fostering the transfer of know-how to user communities. (WP1,
WP2, WP3)