Antiplaque Effect of Essential Oils and 0.2% Chlorhexidine on an In Situ Model of Oral Biofilm Growth: A Randomised Clinical Trial

This work was supported by project PI11/ 01383 from Carlos III Institute of Health (General Division of Evaluation and Research Promotion, Madrid, Spain), which is integrated in National Plan of Research, Development and Innovation (PN I+D+I 2008-2011). This project was cofinanced by European Regional Development Fund (ERDF 2007- 2013

Automatic Compiler-Inserted I/O Prefetching for Out-of-Core Applications

Current operating systems offer poor performance when a numeric application's working set does not fit in main memory. As a result, programmers who wish to solve "out-of-core" problems efficiently are typically faced with the onerous task of rewriting an application to use explicit I/O operations (e.g., read/write). In this paper, we propose and evaluate a fully-automatic technique which liberates the programmer from this task, provides high performance, and requires only minimal changes to current operating systems. In our scheme, the compiler provides the crucial information on future access patterns without burdening the programmer, the operating system supports non-binding prefetch and re- lease hints for managing I/O, and the operating sys- tem cooperates with a run-time layer to accelerate performance by adapting to dynamic behavior and minimizing prefetch overhead. This approach maintains the abstraction of unlimited virtual memory for the programmer, gives the compiler the flexibility to aggressively move prefetches back ahead of references, and gives the operating system the flexibility to arbitrate between the competing resource demands of multiple applications. We have implemented our scheme using the SUIF compiler and the Hurricane operating system. Our experimental results demonstrate that our fully-automatic scheme effectively hides the I/O latency in out-of- core versions of the entire NAS Parallel benchmark suite, thus resulting in speedups of roughly twofold for five of the eight applications, with one application speeding up by over threefold

Solving Large Problems Quickly: Progress in 2001-2003

This document describes the progress we have made and the lessons we have learned in 2001 through 2003 under the NASA grant entitled "Solving Important Problems Faster". The long-term goal of this research is to accelerate large, irregular scientific applications which have enormous data sets and which are difficult to parallelize. To accomplish this goal, we are exploring two complementary techniques: (i) using compiler-inserted prefetching to automatically hide the I/O latency of accessing these large data sets from disk; and (ii) using thread-level data speculation to enable the optimistic parallelization of applications despite uncertainty as to whether data dependences exist between the resulting threads which would normally make them unsafe to execute in parallel. Overall, we made significant progress in 2001 through 2003, and the project has gone well