High Performance Computing
In compute intensive applications, maximizing the performance of limited hardware resources will always be a fundamental challenge. Be it numerical solution of partial differential equations or Monte Carlo integration to compute the multidimensional definite integral of some interesting function.
Since the beginning of the computer era, technologists, programmers and scientists have composed careful instructions to the CPU, aiming to solve ever more challenging problems while spending less time and energy during program execution. High Performance Computing (HPC) is the craft of spreading compute load across several kernels, cores, and computers, and at the same time ensuring that the hardware is operating close to peak capacity.
We have expertise in building distributed Beowulf-style clusters, and writing numerical software that utilizes the combined compute power of supercomputers for non-trivial parallel computing tasks, such as solving large and sparse linear systems of equations across machines. Typically, MPI (Message Passing Interface) is used to divide computations across machines, whereas OpenMP or multithreading is used to facilitate shared memory computations across cores.
Since the main objective of HPC programming is to speed up computations, low level languages like C/C++ and Fortran are generally needed. Our consultants have years of hands-on experience in using these languages both from industry and former academic careers. Over the years, we have developed HPC software in order to study processes that span from water discharge in nature to the formation of the universe.
Andreas submitted his master’s thesis in applied mathematics from the University of Oslo and Simula Research Laboratory. In his thesis he investigated numerical schemes, for solving equations describing Fluid-Structure Interaction, using Python and FEniCS. His academic background has given him several tools and approaches for solving complex problems in a computational/software domain.
Ata holds a PhD in physics with specialisation in astrophysics which he obtained from Brown University in 2014. Before joining the Expert Analytics team, he has worked as a postdoctoral researcher at the University of Oslo and Universite Paris VII. His expertise includes statistical analysis of large data sets, numerical modelling, signal processing, imaging, and programming.
Diako holds a Ph.D. in Computational Mathematics from the University of Oslo. As a student at both Mathematics and Physics departments at the University of Oslo, he has acquired a broad knowledge in various physical and mathematical theories, and numerical methods.
Eigil submitted his master’s thesis in computer science in 2017 after completing a bachelor’s degree in applied mathematics. In his thesis he studied the application of databases to identify higher-level semantics in event data.
Eivind has a masters degree in Computational Science from the University of Oslo, completed in 2016. His project investigated a particle system modeling linear elasticity, and accelerating linear algebra computations using GPUs. From the studies leading to his degree he has gained broad knowledge about algorithms, numerical mathematics, and programming in several languages.
Analyst, strategist and technology enthusiast.
Broad industry insight and project management experience from cross-industry collaboration projects, business development, research strategy, and project planning and execution.
Martin is an expert scientific programmer with a PhD in computational science and more than a decade of software engineering experience from research and industry. This combination of a solid educational background in mathematics and computer science, research and supervision experience, and lots of practical software engineering experience allows him to tackle most development problems as a team player or independently if need be.
Pia is a physicist with more than ten years of experience in scientific programming and data analysis. She holds a PhD in physics, which she obtained from the University of Freiburg, Germany in 2010. She has been working as a researcher, mentor and lecturer in astrophysics at different research institutions across Europe before she joined Expert Analytics in 2018. Her areas of expertise include numerical simulations of complex physical systems, statistical data analysis and signal processing, as well machine learning applications and visualization and handling of large datasets.
Roar has a master’s degree in High Energy Physics from the University of Oslo, completed in 2018. In his thesis he studied two different models of particle production at high energies, one statistical using the thermodynamical equations and one using the properties of a theoretical particle called Pomeron.
Robert has a PhD in astrophysics, with a specialisation in cosmological simulations. He is experienced with numerical modelling of physical systems, statistical analysis of large data sets, high-performance computing, and cloud based applications.
Robert Solli is a specialist in scientific programming, with expertise in mathematical optimisation, statistical analysis and machine learning. He has solved a varied set of problems with this skillset, from understanding complex physical systems to increasing student volunteer participation.
Trygve holds a master’s degree in Industrial Mathematics at NTNU from 2015, and a Ph.D. in Computational Mathematics at the University of Oslo from 2019. In his thesis Trygve developed, analysed and implemented efficient algorithms for solving systems of equations related to fluid flow in the brain.
Vinzenz is a curious, pragmatic, creative problem solver. He holds a PhD in biomechanical engineering, focusing on stochastic simulations of the blood flow in the human arterial system. This interdisciplinary work included working within engineering, medicine, biology, software development and statistics.