Adaptive data placement in an embedded multiprocessor thread library

Embedded multiprocessors pose new challenges in the design and implementation of embedded software. This has led to the need for programming interfaces that expose the capabilities of the underlying hardware. In addition, for systems that implement applications consisting of multiple concurrent threads of computation, the optimized management of inter-thread communication is crucial for realizing high-performance. This paper presents the design of an application-adaptive thread library that conforms to the IEEE POSIX 1003.1c threading standard (Pthreads). The library adapts the placement of both explicitly marked application data objects, as well as implicitly created data objects, in a physically distributed on-chip memory architecture, based on the application's data access characteristics

Smart messages: A system architecture for large networks of embedded systems

A system architecture and a computing model for computation and communication in large networks of embedded systems is proposed. In this model, communication is realized by sending Smart Messages (SMs) in the network. The architecture is meant to provide a pervasive computing infrastructure for networks of embedded systems

Approximate computation with outlier detection in Topaz

We present Topaz, a new task-based language for computations that execute on approximate computing platforms that may occasionally produce arbitrarily inaccurate results. Topaz maps tasks onto the approximate hardware and integrates the generated results into the main computation. To prevent unacceptably inaccurate task results from corrupting the main computation, Topaz deploys a novel outlier detection mechanism that recognizes and precisely reexecutes outlier tasks. Outlier detection enables Topaz to work effectively with approximate hardware platforms that have complex fault characteristics, including platforms with bit pattern dependent faults (in which the presence of faults may depend on values stored in adjacent memory cells). Our experimental results show that, for our set of benchmark applications, outlier detection enables Topaz to deliver acceptably accurate results (less than 1% error) on our target approximate hardware platforms. Depending on the application and the hardware platform, the overall energy savings range from 5 to 13 percent. Without outlier detection, only one of the applications produces acceptably accurate results.United States. Defense Advanced Research Projects Agency (Grant FA8650- 11-C-7192

Electronic textiles: A platform for pervasive computing

The invention of the Jacquard weaving machine led to the concept of a stored "program" and "mechanized" binary information processing. This development served as the inspiration for C. Babbage's analytical engine - the precursor to the modern-day computer. Today, more than 200 years later, the link between textiles and computing is more realistic than ever. In this paper, we look at the synergistic relationship between textiles and computing and identify the need for their "integration" using tools provided by an emerging new field of research that combines the strengths and capabilities of electronics and textiles into one: electronic textiles, or e-textiles. E-textiles, also called smart fabrics, have not only "wearable" capabilities like any other garment, but also have local monitoring and computation, as well as wireless communication capabilities. Sensors and simple computational elements are embedded in e-textiles, as well as built into yarns, with the goal of gathering sensitive information, monitoring vital statistics, and sending them remotely (possibly over a wireless channel) for further processing. The paper provides an overview of existing efforts and associated challenges in this area, while describing possible venues and opportunities for future research. © 2003 IEEE