{"id":364241,"date":"2017-02-21T09:00:14","date_gmt":"2017-02-21T17:00:14","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?p=364241"},"modified":"2018-02-28T13:06:48","modified_gmt":"2018-02-28T21:06:48","slug":"2017-swiss-joint-research-center","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/en-us\/research\/blog\/2017-swiss-joint-research-center\/","title":{"rendered":"From improving a golf swing to reducing energy in datacenters"},"content":{"rendered":"

2017 Swiss Joint Research Center kick off<\/h3>\n

By Scarlet Schwiderski-Grosche (opens in new tab)<\/span><\/a>, Senior Research Program Manager<\/em><\/p>\n

Attendees of the 2017 Swiss Joint Research Center Workshop in Cambridge, UK.<\/p><\/div>\n

\"MSR

(left to right) Aurelien Lucchi and Sebastian Stich, Postdoctoral Researchers at ETH Zurich and EPFL, and Martin Jaggi, Assistant Professor at EPFL, at the workshop.<\/p><\/div>\n

Recently, we celebrated an important milestone for our Swiss Joint Research Center (Swiss JRC). We welcomed top researchers from all partners to a workshop at the Microsoft Research Cambridge Lab (opens in new tab)<\/span><\/a>, to kick off a new phase in our collaboration. This workshop represented the end of a busy 10-month period for the Swiss JRC during which we ramped down projects from the first phase, and conducted a Call for Proposals for the selection of projects for the second phase. At the workshop, researchers from the Swiss JRC presented their selected proposals to kick off the collaborations in the new funding cycle.<\/p>\n

First, a little background. The Swiss JRC is a collaborative research engagement between Microsoft Research and the two universities that make up the Swiss Federal Institutes of Technology:\u00a0ETH Zurich (opens in new tab)<\/span><\/a>\u00a0(Eidgen\u00f6ssische Technische Hochschule Z\u00fcrich<\/em>, which serves German-speaking students) and\u00a0EPFL\u00a0 (opens in new tab)<\/span><\/a>(\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne<\/em>, which serves French-speaking students). The Swiss JRC is a continuation of a collaborative engagement that began back in 2009, when the same three partners embarked on ICES (Innovation Cluster for Embedded Software (opens in new tab)<\/span><\/a>) and was renewed for another five years in 2014. Basically, university researchers collaborate with Microsoft researchers to solve problems in computer science.<\/p>\n

\"Microsoft

Pamela Delgado, PhD student on the EPFL project with Florin Dinu, “Towards Resources-Efficient Data Centers”<\/p><\/div>\n

With this workshop, the Swiss JRC kicked off 10 projects, four between ETH Zurich and Microsoft and six between EPFL and Microsoft. These projects were chosen from 20 proposals assessed by the Swiss JRC steering committee for their intellectual merit, potential scientific and societal impact and evidence of strong collaborative interest between the project partners.<\/p>\n

One compelling project uses drones that follow you around while you ski or play golf, then gives you feedback for improvement of your form\u2014think of it as a personal trainer\/GoPro\/drone combo that can both figure out how to video you while you do an activity, as well as analyze your performance and make recommendations for improvements. Another drone-based project (or as we like to call them, micro-aerial vehicles, or MAVs), makes the MAV easier to control via a solution-based approach, versus movement-based controls. This project asks, \u201cWhat is the goal of the MAV flight?\u201d and solves for that, versus making the operator think about both \u201cWhere should this MAV go?\u201d and \u201cWhat should it do while it\u2019s flying?\u201d<\/p>\n

\"Microsoft

Babak Falsafi, Professor of Computer and Communication Sciences, EPFL<\/p><\/div>\n

Other projects address new requirements in the data center, aiming at making data processing more efficient and essentially helping to reduce energy usage. One set of projects assesses data-intensive applications as are common in, for example, machine learning, graph processing, and bioinformatics. These projects explore near-memory processing, better server utilization, improved data clustering, and new approaches to transactional processing. Another set of projects leverages new hardware architectures based on, for example, FPGAs (Field Programmable Gate Arrays) and DRAM (Dynamic Random-Access Memory). Some projects address mechanisms to off-load expensive computations to achieve massive parallelism or to co-locate different stages of deep learning on the same platform. All of these projects propel the leading edge of artificial intelligence.<\/p>\n

\u201cEmerging silicon technologies provide an opportunity to offload data management services to near-memory accelerators for better performance. Through several Microsoft Research collaborations, including this funding round\u2019s NeMeSys project, we are rapidly propelling the state-of-the-art in near-memory processing.\u201d\u00a0\u2013\u00a0Babak Falsafi, Professor of Computer and Communication Sciences, EPFL<\/p><\/blockquote>\n

Here\u2019s the list of projects and their principal investigators:<\/p>\n

Data Science with FPGAs in the Data Center<\/strong>
\nGustavo Alonso, ETH Zurich
\nKen Eguro, Microsoft Research, Redmond lab<\/p>\n

Human-Centric Flight II: End-user Design of High-level Robotic Behavior<\/strong>
\nOtmar Hilliges, ETH Zurich
\nMarc Pollefeys, Microsoft Analog Research & Development<\/p>\n

Tractable by Design<\/strong>
\nThomas Hofmann and Aurelien Lucchi, ETH Zurich
\nSebastian Nowozin, Microsoft Research, Cambridge lab<\/p>\n

Enabling Practical, Efficient and Large-Scale Computation Near Data to Improve the Performance and Efficiency of Data Center and Consumer Systems<\/strong>
\nOnur Mutlu and Luca Benini, ETH Zurich
\nDerek Chiou, Microsoft Relevance and Intent, Research &Development<\/p>\n

Towards Resource-Efficient Data Centers<\/strong>
\nFlorin Dinu, EPFL
\nChristos Gkantsidis and Sergey Legtchenko, Microsoft Research, Cambridge lab<\/p>\n

Near-Memory System Services<\/strong>
\nBabak Falsafi, EPFL
\nStavros Volos, Microsoft Research, Redmond lab<\/p>\n

Coltrain: Co-located Deep Learning Training and Inference<\/strong>
\nBabak Falsafi and Martin Jaggi, EPFL
\nEric Chung, Microsoft Research, Redmond lab<\/p>\n

From Companion Drones to Personal Trainers<\/strong>
\nPascal Fua and Mathieu Salzmann, EPFL
\nDebadeepta Dey, Ashish Kapoor, and Sudipta Sinha, Microsoft Research, Redmond lab<\/p>\n

Revisiting Transactional Computing on Modern Hardware<\/strong>
\nRachid Guerraoui and Georgios Chatzopoulos, EPFL
\nAleksandar Dragojevic, Microsoft Research, Cambridge lab<\/p>\n

Fast and Accurate Algorithms for Clustering<\/strong>
\nMichael Kapralov and Ola Svensson, EPFL
\nYuval Peres, Nikhil Devanur and Sebastien Bubeck, Microsoft Research, Redmond lab<\/p>\n

Related:<\/strong><\/p>\n