Extending Saiph to simulate fluid mechanics and chemistry problems

Saiph is a domain specific language for solving partial differential equations in high performance computing systems, developed at the Barcelona Computing Center. The aim of this project is to extend this language to support fluid mechanics and chemistry problems

Extending Saiph to simulate fluid mechanics and chemistry problems

Saiph is a domain specific language for solving partial differential equations in high performance computing systems, developed at the Barcelona Computing Center. The aim of this project is to extend this language to support fluid mechanics and chemistry problems

Examen Final

Resolve

Combining one-sided communications with task-based programming models

Hybrid programming combining task-based and message-passing models is an increasingly popular technique to exploit multi-core clusters. The Task-Aware MPI (TAMPI) library integrates both models enabling the safe overlap of computation and communication tasks using two-sided MPI communications. Two-sided primitives combine data transfers with implicit synchronizations, but one-sided models usually offer more efficient data transfers decoupling synchronizations. MPI offers four distinct one-sided synchronization modes, while GASPI is a PGAS API providing one-sided operations with remote notifications for fine inter-process synchronizations.In this paper, we study the challenges of integrating MPI and GASPI one-sided operations with the OpenMP and OmpSs-2 tasking models. We propose and implement several extensions to the GASPI and OmpSs-2 programming models, which are leveraged by a new library called Task-Aware GASPI (TAGASPI). The TAGASPI library allows the efficient and safe use of one-sided operations with remote notifications inside tasks. Both TAGASPI and TAMPI transparently manage communications issued by tasks and allow these to overlap with computation tasks naturally, following a data-flow model. These libraries are complementary and can be mixed in the same application.Our experience porting several mini-apps to this hybrid model shows that TAGASPI helps leverage one-sided communications with similar complexity to pure and hybrid two-sided MPI approaches. We show that our hybrid one-sided approach outperforms the pure MPI strategies, but it also surpasses the TAMPI’s performance when stressing communication phases, e.g., increasing the communication parallelism and reducing the communication tasks’ sizes.This work has been supported by the European Union H2020 Programme through the LoSync PRACE6IP project (agreement No. INFRAEDI-823767); the Spanish Ministry of Economy through the Severo Ochoa Center of Excellence Program (SEV-2015-0493); the Spanish Ministry of Science and Innovation (PID2019-107255GB); and the Generalitat de Catalunya (2017-SGR-1414).Peer ReviewedPostprint (author's final draft

Automated generation of high-performance computational fluid dynamics codes

Domain-Specific Languages (DSLs) improve programmers productivity by decoupling problem descriptions from algorithmic implementations. However, DSLs for High-Performance Computing (HPC) have two additional critical requirements: performance and scalability. This paper presents the automated process of generating, from abstract mathematical specifications of Computational Fluid Dynamics (CFD) problems, optimised parallel codes that perform and scale as manually optimised ones. We consciously combine within Saiph, a DSL for solving CFD problems, low-level optimisations and parallelisation strategies, enabling high-performance single-core executions which effectively scale to multi-core and distributed environments. Our results demonstrate how high-level DSLs can offer competitive performance by transparently leveraging state-of-the-art HPC techniques.This research has received funding from the European Union’s Horizon 2020/EuroHPC research and innovation programme under grant agreement N. 955606 (DEEP-SEA), and is supported by the Spanish State Research Agency - Ministry of Science and Innovation (contract PID2019-107255 GB), and by the Generalitat de Catalunya (2017-SGR1414). This work is also supported by the Ministry of Economy of Spain through Severo Ochoa Center of Excellence Program (SEV-2015-0493).Peer ReviewedPostprint (author's final draft