Past Research Seminars

Tuesday, 11 July, 2017

The most common software update on the AppStore *by far* is "Bug fixes and performance enhancements." Now that Moore's Law Free Lunch has ended, programmers have to work hard to get high performance for their applications. But why is performance so hard to deliver?

Tuesday, 27 June, 2017

Monday, 12 June, 2017

This talk will discuss recent technologies that Bruce Jacob and his group have helped to develop in high-performance systems, including Micron’s Hybrid Memory Cube, flash-based main memories, and high-bandwidth/high-capacity memory, and will discuss the impact of tomorrow’s memory technologies on tomorrow’s applications and operating systems.

Wednesday, 07 June, 2017

This talk will cover the technical features of the RISC-V ISA design, which has the goals of scaling from the tiniest implementations for IoT up to the largest warehouse-scale computers, with support for extensive customization. We'll also describe industry-competitive open-source cores developed at UC Berkeley, all written in Chisel, a productive new open-source hardware design language.

Friday, 02 June, 2017

This workshop, supported by the Spanish Supercomputing Network, is dedicated to getting together combustion researchers across the country, and share experiences and issues related to the modelling of combustion systems.

Thursday, 25 May, 2017 to Friday, 26 May, 2017

Scientific Workshop supported by the Spanish Supercomputing Network

Thursday, 25 May, 2017

In this lecture, organised in collaboration with UPC, Dr Vargas will explore the key challenges and opportunities for data management in the new scientific world, and discuss how a possible data centric artificial intelligence community can best contribute to these exciting domains.

Thursday, 18 May, 2017

In the Big Data era, due to the ever-growing graph scale and algorithm complexity, several distributed graph processing frameworks have attracted many interests from both academia and industry. In this talk, will be investigated how to achieve the trade-off between performance and cost for large scale graph processing on the Cloud.

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