Methodologies and tools for performance analysis and optimization

Machine learning techniques are used to model and optimize the performance of parallel agent-based applications. Includes load balancing, tuning, and benchmarking.

Institution:

Research Group:

High Performance Computing Applications for Science and Engineering (HPCA4SE)

Researcher/s:

Anna Sikora, Eduardo César

Description:

performance models using machine learning (ML) techniques. Characterization study of parallel OpenMP regions through hardware counters. Development of tuning techniques for parallel agent-based modeling (ABM) applications. Optimization of the distribution of agents according to their computational load and communication pattern. Benchmark to evaluate agent-based development platforms.

Value Proposition:

parallel computing, distributed computing, HPC+AI convergence, machine learning.

Aplication areas:

Biomedicine, engineering, finance

Target market:

agent-based applications

Technology Readiness Level (1-9): N/A

More information

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