Bio
Lev is an experienced systems administrator, specialising in the Linux operating system and scientific applications, a project manager, systems engineer, and quality management systems coordinator, specifically for ISO 9001 (Quality assurance) and ISO 270001 (Information Technology Security). He also does a lot of training for researchers and technical staff in Linux, High Performance Computing, mathematical programming, Postgresql, and related subjects, with graduates and post-doctoral researchers from a variety of organisations
Lev works for the Research Platforms group at the University of Melbourne as the Senior High Performance Computing Support and Training Officer, and prior to that Victorian Partnership for Advanced Computing, as a systems administrator for Linux clusters
Complex Problems Actually Have Complex Solutions: Data and Processing Challenges for New Zealand
Lev Lafayette
HPC SysAdmin
University of Melbourne, Australia
Wednesday 19 February 2020 – 1:45 pm
Abstract
A continuing issue in the field of computing is our capacity to store, transfer, and processing increasingly large datasets and increasingly complex problems. This is, of course, a fundamental reason why there has been developments in multicore computing and in various implementations of parallel programming. New Zealand is by no means immune to these changes and faces a number of big data and complex problem issues in its own right, especially relating to geography and climate, which by necessity have enormous impacts on the economy. Yet, almost parallel to this many IT managers express a desire for applications that are feature-rich but easy to utilise whilst politicians often engage with the problems an assumption of stability (the fate of the Melomys rubicola is a particularly pertinent case). Unsurprisingly to those coming from an engineering perspective, these desires and assumptions are fraught with problems.
Despite some impressive technical developments over the years to improve performance and clarity, we keep coming back to the fundamental issue that complex problems actually have complex solutions, and avoiding massive failures in information systems and research reproducibility requires infrastructure, quality assurance, and training. Examples for a New Zealand context are provided.
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VIDEO
multicore.world 