ABA-Based Programs for Children Diagnosed With Autism Spectrum Disorder: Parental and Professional Experiences at School and at Home

Having a child diagnosed with Autism Spectrum Disorder (ASD) poses a range of challenges to families, many of which can be addressed through appropriate intervention. A study of parental (n = 95) and professional (n = 67) experiences was carried out in relation to two settings: (a) schools that provided intensive interventions based on the science of Applied Behavior Analysis (ABA), and (b) non-intensive ABA-based home programs. Results show that parents whose children attend ABA-based schools were generally more satisfied with their child's educational provision, monitoring procedures, and level of staff training, than parents who were not offered ABA-based education in schools. © 2012 Copyright Taylor and Francis Group, LLC.

A profile-based tool for finding pipeline parallelism in sequential programs

Traditional static analysis fails to auto-parallelize programs with a complex control and data flow. Furthermore, thread-level parallelism in such programs is often restricted to pipeline parallelism, which can be hard to discover by a programmer. In this paper we propose a tool that, based on profiling information, helps the programmer to discover parallelism. The programmer hand-picks the code transformations from among the proposed candidates which are then applied by automatic code transformation techniques.

This paper contributes to the literature by presenting a profiling tool for discovering thread-level parallelism. We track dependencies at the whole-data structure level rather than at the element level or byte level in order to limit the profiling overhead. We perform a thorough analysis of the needs and costs of this technique. Furthermore, we present and validate the belief that programs with complex control and data flow contain significant amounts of exploitable coarse-grain pipeline parallelism in the program’s outer loops. This observation validates our approach to whole-data structure dependencies. As state-of-the-art compilers focus on loops iterating over data structure members, this observation also explains why our approach finds coarse-grain pipeline parallelism in cases that have remained out of reach for state-of-the-art compilers. In cases where traditional compilation techniques do find parallelism, our approach allows to discover higher degrees of parallelism, allowing a 40% speedup over traditional compilation techniques. Moreover, we demonstrate real speedups on multiple hardware platforms.

Parallel Programming of General-Purpose Programs Using Task-Based Programming Models

The prevalence of multicore processors is bound to drive most kinds of software development towards parallel programming. To limit the difficulty and overhead of parallel software design and maintenance, it is crucial that parallel programming models allow an easy-to-understand, concise and dense representation of parallelism. Parallel programming models such as Cilk++ and Intel TBBs attempt to offer a better, higher-level abstraction for parallel programming than threads and locking synchronization. It is not straightforward, however, to express all patterns of parallelism in these models. Pipelines are an important parallel construct, although difficult to express in Cilk and TBBs in a straightfor- ward way, not without a verbose restructuring of the code. In this paper we demonstrate that pipeline parallelism can be easily and concisely expressed in a Cilk-like language, which we extend with input, output and input/output dependency types on procedure arguments, enforced at runtime by the scheduler. We evaluate our implementation on real applications and show that our Cilk-like scheduler, extended to track and enforce these dependencies has performance comparable to Cilk++.