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--- funding [2009/07/01 07:44]
pollock
+++ funding [2013/05/03 14:40]
pollock [NSF 0720712 Collaborative: CSR-AES: System Support for Auto-tuning MPI Applications]
@@ Line 1: / Line 1: @@
-====== Overview ======
+====== Funding Overview ======
 The research in the Software Analysis and Compilation Lab at University of Delaware
 is funded through research grants and student fellowships. Throughout the years, funding has been provided by:
-  * NSF - The National Science Foundation
+  * [[http://www.nsf.gov|NSF - The National Science Foundation]]
-  * CTA - Army Research Lab Collaborative Technology Alliance
+  * [[http://www.arl.army.mil/www/default.cfm?Action=93|CTA - Army Research Lab Collaborative Technology Alliance]]
-  * ARL - The Army Research Laboratory
+  * [[http://www.arl.army.mil/www/default.htm|ARL - The Army Research Laboratory]]
-  * CRA-W - The Computing Research Association's Committee on the Status of Women in Computing Distributed Mentoring Program (DMP, DREU)
+  * [[http://www.cra-w.org/dmp|CRA-W - The Computing Research Association's Committee on the Status of Women in Computing Distributed Mentoring Program (DMP, DREU)]]
-====== Summaries of Current Research Grants ======
+====== Current Research Grants ======
-=== NSF 0702401 Applying and Integrating Natural Language Processing Analysis of Programs to Aid in Software Maintenance and Evolution ===
+==== NSF 0702401 Applying and Integrating Natural Language Processing Analysis of Programs to Aid in Software Maintenance and Evolution ====
+//PI: Lori Pollock; Co-PI: Vijay Shanker//
 Due to the unprecedented size and complexity of modern software and increased code reuse, between 60-90% of resources are devoted to modifying an application to meet new requirements and to fix discovered bugs. To locate bugs or modify an application, developers must identify the high-level idea, or concept, to be changed and then locate, comprehend, and carefully modify the concept s concern, or implementation, in the code. Software engineers increasingly rely on available software tools to automate maintenance tasks as much as possible; however, despite all of the available automated support, recent studies have shown that more development time is spent reading, locating, and comprehending code than actually writing code.
@@ Line 32: / Line 33: @@
+=== REU Supplements ===
+/05/2009 2 Undergraduates
+/06/2007 2 Undergraduates
+==== NSF 0509170 CSR - AES: An Integrated Approach to Improving Communication Performance in Clusters ====
+//PI: Martin Swany; Co-PI: Lori Pollock//
+The project will develop an integrated aproach to improving communication performance in clusters. Cluster computing has become a common, cost-effective means of parallel computing. Although adding more CPUs increases the cluster's maximum processing power, real applications often can not efficiently use very large numbers of CPUs, due to lack of scalability. In regular codes the main impediment to achieving scalability is the communication overhead which increases as the number of CPUs increases. Most of these optimization methods proposed target specialized hardware or programming languages, and require specialized knowledge from the domain scientist, or are not enough to provide a comprehensive solution on their own, and do not adequately address the challenges of the layers of communication software between the sender processes and the receiver processes. Improved performance overall for these applications, it remains largely untapped due to (1) the need for the knowledge of the context of the communication operations to exploit the sophisticated network technology fully, and the (2) the low level nature of programming needed within the application program context to achieve that potential. In particular, performance can often be improved through increasing the use of lightweight asynchronous communication. Unfortunately, programming with asynchronous communication is difficult and error prone, even for the most experienced programmers.
+The project will pursue a vertically integrated approach, where a set of optimizations in the compiler, network and operating system, can enable legacy parallel applications to scale to a much larger number of CPUs, even if written without any knowledge of our techniques. An experimental prototype and preliminary experiments with real scientific applications, show that significant performance improvements are possible with a vertically integrated approach where knowledge of the context of communication operations is joined with knowledge of the network and cluster details to provide a fine-grained strategy for overlapping communication and computation. Based on these initial promising results, the overall goal of this proposed research is to create a means for scalable cluster computing through enabling integrated knowledge and cooperation between the source optimizer, operating system, and network technology of the cluster, without relying on the programmer to learn about the low level details of the cluster communications system.