Optimization of condensed matter physics application with OpenMP tasking model

The Density Matrix Renormalization Group (DMRG++) is a condensed matter physics application used to study superconductivity properties of materials. It’s main computations consist of calculating hamiltonian matrix which requires sparse matrix-vector multiplications. This paper presents task-based parallelization and optimization strategies of the Hamiltonian algorithm. The algorithm is implemented as a mini-application in C++ and parallelized with OpenMP. The optimization leverages tasking features, such as dependencies or priorities included in the OpenMP standard 4.5. The code refactoring targets performance as much as programmability. The optimized version achieves a speedup of 8.0 × with 8 threads and 20.5 × with 40 threads on a Power9 computing node while reducing the memory consumption to 90 MB with respect to the original code, by adding less than ten OpenMP directives.This work is partially supported by the Spanish Government through Programa Severo Ochoa (SEV2015-0493), by the Spanish Ministry of Science and Technology (project TIN2015-65316-P), by the Generalitat de Catalunya (contract 2017-SGR-1414) and by the BSC-IBM Deep Learning Research Agreement, under JSA “Application porting, analysis and optimization for POWER and POWER AI”. This work was partially supported by the Scientific Discovery through Advanced Computing (SciDAC) program funded by U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research and Basic Energy Sciences, Division of Materials Sciences and Engineering. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.Peer ReviewedPostprint (author's final draft

Performance analysis and optimization of an HPC application: DMRG++

DMRG++ (Density Matrix Renormalization Group) és una aplicació de física de la matèria condensada orientada a HPC, originalment desenvolupada per l'Oak Ridge National Laboratory (ORNL). En aquest projecte es treballarà en la millora de la part de càlcul intensiu de l'aplicació, fent ús d'una miniapp que encapsula aquesta secció crítica. Partint d'una implementació inicial amb OpenMP basada en diversos parallel for aniuats, s'exploraran diferents alternatives per millorar el temps d'execució i el consum de memòria mitjançant el model de tasques amb dependències d'OpenMP, tot fent servir una estratègia d'anàlisi de l'aplicació i de desenvolupament iterativa. D'aquesta manera, no només esperem contribuir amb la millora d'una aplicació científica, sinó també mostrar tècniques d'anàlisi efectives i estratègies de paral·lelització per a aplicacions amb distribucions de feina molt desiguals.DMRG++ (Density Matrix Renormalization Group) is a condensed matter physics application oriented to HPC, developed by Oak Ridge National Laboratory (ORNL). In this project, we will focus on improving the intensive arithmetic kernel of the application, using a miniapp that encapsulates this critical program part. Starting with an initial implementation with OpenMP, which uses several nested parallel for, we will explore different alternatives to improve its execution time and memory consumption through OpenMP task dependency model, taking advantage of an iterative strategy of in-depth application analysis and development. In this way, we are not just contributing by improving a scientific application, but also showing effective analysis techniques and best practices for programmability and parallelization focused on applications with irregular workloads