{"id":932,"date":"2012-01-25T16:29:36","date_gmt":"2012-01-25T20:29:36","guid":{"rendered":"https:\/\/www.bu.edu\/hic\/?p=932"},"modified":"2014-07-01T11:20:49","modified_gmt":"2014-07-01T15:20:49","slug":"mghpcc-seed-grants","status":"publish","type":"post","link":"https:\/\/www.bu.edu\/hic\/2012\/01\/25\/mghpcc-seed-grants\/","title":{"rendered":"MGHPCC Awards Seed Grants to Institute Members"},"content":{"rendered":"

Three research projects involving several Hariri Institute members have recently received \u201cseed grants\u201d for projects related to the Massachusetts Green High Performance Computing Center<\/a> (MGHPCC).\u00a0MGHPCC is a groundbreaking collaboration of five of the state\u2019s most research-intensive universities\u2014Boston University, MIT, Harvard, Northeastern University, and the University of Massachusetts\u2014along with both\u00a0state government and private industry, in the most significant collaboration among government, industry and public and private universities in the history of the Commonwealth, and the first facility in the nation of its kind.<\/p>\n

As part of the launch of MGHPCC, a competitive award process selected several seed projects to begin work on research using the kinds of high-performance systems to be available at the Center. Three of those projects involved Boston University faculty members, combining support from the seed grant program, the Provost’s Office, and the Hariri Institute. The three BU projects are:<\/p>\n

Designing Green Software for High Performance Computing Clusters
\n<\/strong><\/em>Ayse K. Coskun (BU), Gunar Schirner (NE), Martin C. Herbordt (BU)<\/p>\n

Energy efficiency is one of the central societal and technical issues today, and has become yet more critical with increased focus on the environment and the world\u2019s climate. Power consumption is also the major limit in improving computing performance. Large computing clusters already have prohibitive operational and cooling costs. In addition, further increases in processor power densities are not viable as they breach the reliable operating temperatures of computing hardware. These limitations on power consumption and cooling are bringing to an end the historic performance scaling in high performance computing (HPC) centers, which has so far enabled tremendous advancements in solving complex scientific problems. <\/p>\n

This project’s research goal is to design systematic, inexpensive methods to optimize the application software for increasing the energy efficiency. HPC software has been traditionally optimized for performance, and little has been done for generating better software for energy efficient operation. As part of the research plan, the project will demonstrate proof-of-concept of novel “green software” techniques on real-life HPC applications.<\/p>\n

Tree and Multipole Algorithms for Exascale Computing
\n<\/strong><\/em>Lorena Barba (BU),\u00a0Cris Cecka (Harvard),\u00a0Hans Johnston (University of Massachusetts, Amherst)<\/p>\n

This project is a collaboration among investigators in BU, Harvard and\u00a0UMass aimed at creating an open and high-performance software\u00a0infrastructure for a family of hierarchical N-body algorithms. “N-\u00a0body” is the name given to any problem that involves a system where\u00a0each object depends on the state of every other object in the system.\u00a0The classic example in mechanics is gravitational interaction, but the\u00a0situation also appears in the interactions of atoms or ions and in\u00a0discrete representations of the equations for acoustics,\u00a0electromagnetics and fluid dynamics. Algorithms to solve this problem\u00a0that use hierarchical groupings of the objects in the system (or\u00a0points in the discretization) are often fast, and scale very well in\u00a0highly parallel computers. In fact, some believe that these algorithms\u00a0will be better suited to the increasing numbers of cores in high-\u00a0performance computers, and more likely to reach exascale. What is\u00a0lacking is a concerted effort to create high-performance software\u00a0offering the power of these algorithms to the wider scientific\u00a0community. <\/p>\n

The team funded by this seed grant will develop software\u00a0infrastructure for hierarchical N-body algorithms aimed at the top\u00a0computing systems, such as Blue Gene (for which the support of IBM as\u00a0an industrial partner will be instrumental) and GPUs. The team will\u00a0also develop capability to solve diverse problems, including\u00a0biophysics, acoustics and fluid dynamics.<\/p>\n

Clinical Elastic High Performance Computing
\n<\/strong><\/em>Jonathan Appavoo (BU), Dr. Ellen Grant (Children’s Hospital and Harvard University)<\/p>\n

One of the challenges in analyzing radiology data by computer is that it typically takes days to get the results, because the processing is computationally intensive. In a clinical setting, doctors and patients would benefit from getting results in seconds. To make this happen, doctors need to call upon massive computational power instantaneously, and they only use it for a short period of time. This kind of bursty use is common in cloud computing, but conventional cloud computing systems don’t have the high-speed interconnection between computers needed to process this kind of data. And conventional high-performance computing systems don’t have the interactive ability that doctors need.<\/p>\n

In this project, Dr. Grant and Prof. Appavoo will investigate putting those pieces together to create systems for on-demand radiological analysis. This research provides Prof. Appavoo a set of real applications to explore his model and mechanisms for \u00a0‘Interactive High-Performance Computing’, and gives Dr. Grant the systems expertise and computational resources to evaluate how well an interactive approach can benefit doctors and patients.<\/p>\n

<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"

Three research projects involving several Hariri Institute members have recently received \u201cseed grants\u201d for projects related to the Massachusetts Green High Performance Computing Center (MGHPCC).\u00a0MGHPCC is a groundbreaking collaboration of five of the state\u2019s most research-intensive universities\u2014Boston University, MIT, Harvard, Northeastern University, and the University of Massachusetts\u2014along with both\u00a0state government and private industry, in the […]<\/p>\n","protected":false},"author":5410,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[11716],"tags":[],"_links":{"self":[{"href":"https:\/\/www.bu.edu\/hic\/wp-json\/wp\/v2\/posts\/932"}],"collection":[{"href":"https:\/\/www.bu.edu\/hic\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.bu.edu\/hic\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/hic\/wp-json\/wp\/v2\/users\/5410"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/hic\/wp-json\/wp\/v2\/comments?post=932"}],"version-history":[{"count":18,"href":"https:\/\/www.bu.edu\/hic\/wp-json\/wp\/v2\/posts\/932\/revisions"}],"predecessor-version":[{"id":3676,"href":"https:\/\/www.bu.edu\/hic\/wp-json\/wp\/v2\/posts\/932\/revisions\/3676"}],"wp:attachment":[{"href":"https:\/\/www.bu.edu\/hic\/wp-json\/wp\/v2\/media?parent=932"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.bu.edu\/hic\/wp-json\/wp\/v2\/categories?post=932"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.bu.edu\/hic\/wp-json\/wp\/v2\/tags?post=932"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}