Parallel Hybrid Testing Techniques for the Dual-Programming Models-Based Programs

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...

Framework for Testing based Development of Parallel and Distributed Programs

Since testing is an essential part of the software development life cycle, it should be part of the whole development process. Only a few approaches exist for parallel and distributed systems which embed testing in the whole process. Here we present attempts to overcome deficiencies in the development of parallel and distributed programs. It is based on objectoriented design and temporal logic ...

Communication Bandwidth of Parallel Programming Models on Hybrid Architectures

Scalable verification techniques for data-parallel programs

This thesis is about scalable formal verification techniques for software. A verification technique is scalable if it is able to scale to reasoning about real (rather than synthetic or toy) programs. Scalable verification techniques are essential for practical program verifiers. In this work, we consider three key characteristics of scalability: precision, performance and automation. We explore...

Application-Level Checkpointing Techniques for Parallel Programs

In its simplest form, checkpointing is the act of saving a program’s computation state in a form external to the running program, e.g. the computation state is saved to a filesystem. The checkpoint files can then be used to resume computation upon failure of the original process(s), hopefully with minimal loss of computing work. A checkpoint can be taken using a variety of techniques in every l...