Tanya Wen

People adjust how fast they update task rules, depending on the volatility of their environment, by regulating cognitive control accordingly. We investigated whether this adaptation is primarily driven by recently experienced volatility in task demands, or can also be shaped by learned environmental knowledge indicating expected levels of volatility. To this end, we trained participants on a Wisconsin Card Sorting Test task where different environments required different speeds of task rule updating. We demonstrate that, initially, participants adopted task rule updating strategies depending on the most recently experienced levels of volatility and feedback (Experiment 1). However, after extensive (4 days) training (Experiment 2), participants updated task rules using strategies based on developed environmental knowledge. We also show how participants fine‐tuned their task rule updating strategies over learning. In sum, our findings provide important insights into how humans update task rules using different strategies and highlight the importance of multiday training in developing environmental knowledge for the regulation of cognitive control.

Partitioned Global Address Space languages combine the programming convenience of shared memory with the locality and performance control of message passing. One such language, Unified Parallel C is an extension of ISO C defined by a consortium that boasts multiple proprietary and open source compilers. Another PGAS language, Titanium, is a dialect of JavaTM designed for high performance scientific computation. In this paper we describe some of the highlights of two related projects, the Titanium project centered at U.C. Berkeley and the UPC project centered at Lawrence Berkeley National Laboratory. Both compilers use a source-to-source strategy that trans-lates the parallel languages to C with calls to a communication layer called GASNet. The result is portable high-performance compilers that run on a large variety of shared and distributed memory multiprocessors. Both projects combine compiler, runtime, and application efforts to demonstrate some of the performance and productivity advantages to these languages.Copyright 2007 ACM.

We describe the rationale behind the design of key features of Titanium-an explicitly parallel dialect of Java for high-performance scientific programming-and our experiences in building applications with the language. Specifically, we address Titanium's partitioned global address space model, single program multiple data parallelism support, multi-dimensional arrays and array-index calculus, memory management, immutable classes, operator overloading, and generic programming. We provide an overview of the Titanium compiler implementation, covering various parallel analyses and optimizations, Titanium runtime technology and the GASNet network communication layer. We summarize results and lessons learned from implementing the NAS parallel benchmarks, elliptic and hyperbolic solvers using adaptive mesh refinement, and several applications of the immersed boundary method. © 2007 SAGE Publications.