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.
Alexander is a senior software developer specializing in backend and system development in Python. His experience with Python dates back to 2010, and he has been working professionally with system development in Python since 2018. During his career, he has worked in several platform and product teams in both the public transport sector and the energy sector. Alexander holds a master’s thesis in computational quantum physics from the University of Oslo.
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.
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.
Felix is a research scientist with experience in data analysis and scientific programming. He holds a PhD in physics and worked in various interdisciplinary projects both as a Postdoc and Researcher in an academic setting as well as a senior researcher in industry. Felix has a background in both experimental studies as well as mathematical and numerical modelling. His creativity, analytical mindset and scientific experience provide him with a solid foundation for finding solutions to complex problems.
Marco holds a Ph.D in computational Condensed Matter Physics, with a strong focus on quantum and classical atomistic simulation methods. Throughout his decade-long career he has worked on both software development - mainly in C++ and Python - and research intensive projects across several research fields ranging from low-temperature physics to computational chemistry and biophysics. This experience, along with his robust mathematical and coding background, allows him to be a broad and thorough problem solver, well capable of working both independently and as a team member.
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 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.