Where: Calgary, AB, CANADA
Reverse Time Migration: A commercial case study
Join HP and Acceleware for this complimentary lunch and learn as we present the latest GPU accelerated technologies for oil and gas exploration.
Complex geologies and alternative imaging methods require High Performance Computing (HPC) to produce accurate images of the subsurface. Acceleware is at the forefront of HPC technologies for the energy industry. This informative lunch and learn will highlight the powerful role that GPUs play in seismic processing plus information on current capabilities of GPUs and CPUs. A commercial case study of a GPU accelerated version of Reverse Time Migration will be presented.
Attendees will have the opportunity to interact with colleagues, hear from industry experts and gain an insight into the world of GPUs for oil and gas. Technical staff will be available to discuss first-hand the computing challenges facing your organisation.
This is an invitation event for geophysicists, software developers and engineers in the oil and gas industry. Please email us if you would like an invitation!
Lunch & learn speakers
Business Development Manager HPC, HP Canada Co.
HP has a number of systems designed for GPU use - ranging from single cards added to workstations to multi-user, multi GPU enabled clusters Glenn will overview the kinds of systems that facilitate GPU use, highlighting solutions appropriate to the upstream Oil and Gas sector.
RTM Product Manager, Acceleware Ltd.
Darren is the product manager for seismic products in Acceleware, including the GPU-powered Reverse Time Migration and Forward Modeling libraries. He has previously presented on high performance computing and seismic at the SEG and EAGE.
Director of Product Management, Acceleware Ltd.
Chris has successfully launched numerous GPU-based products used by companies world-wide. He is a recognised expert in GPU computing, co-authored the content for CUDA training courses that has been delivered to over 1000 students worldwide and has presented at GPU computing events. In addition to his GPU experience, his background includes parallelization of algorithms on digital signal processors (DSPs).