Software for Multicore and Parallel Computing
Open Parallel offers Solutions for the Data Science Revolution
As data sets become larger and information requirements are time and privacy sensitive, making smarter use of information becomes more complex and outside the core focus of non-specialised organisations.
Applications are demanding more capacity, mixed latency demands, process flexibility as social networking, sensor-networks, scientific research, business models, financial engineering and economic modeling all make big data a common requirement.
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Open Parallel and the SKA radio telescope Pre-construction Phase
Open Parallel specialises in multicore and parallel computing and our vision is to consolidate a global hub in New Zealand and Australia about entrepreneurship based in multicore technologies.
Our work with SKA -the ultimate big-data project, is the leading example: Open Parallel is the work package manager for the Software Development Environment work package for the CSP (Central Signal Processor) element of the SKA -and also contributes to the Science Data Processor (SDP).
(L-R) Nicolás Erdödy (CEO, Open Parallel), Simon Berry (Director of Policy, SKA Organisation, UK), Don Christie (Director, Catalyst) at Catalyst’s HQ in Wellington, during Mr. Berry’s visit to New Zealand (25 March 2015)
To support the vision -and with an economic development agenda, every year we organise Multicore World conferences in New Zealand to create a convergence between industry, academia, science and engineer/developer communities where we build strategic partnerships and learn from each other. Check testimonials
For our 4th edition -and with the formal sponsorship from the SKA Organisation and the Wellington City Council we extended the conference with a workshop “HPC in the Cloud: the SKA example”.
The IV Multicore World was 17th-18th-19th February. Check here the program, speakers and other information. Videos and slides are being posted regularly.
We are already working on the fifth edition (February 2016) and looking at platforms for technical & scientific computing and applications on top of them.
OPEN PARALLEL
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