high performance computing on graphics processing units: hgpu.org

The notion of virtual machine has permeated every aspect of computing systems, as witnessed by the ever growing set of virtual execution systems targeted by programming languages such as Java, C#, Perl and Python just to mention few of them. Virtual machines are appreciated not only because of portability of computer programs across different architectures; the ability of monitoring the program execution has proven important to enforce security aspects as well as tailoring execution onto specific architectures. Moreover, dynamic loading and reflection allow programs to adapt their execution depending on several environment factors, including the underlying computing architecture. Recently microprocessor architectures are shifting from the original Von Neumann computational model, and including different forms of concurrent computation that cannot be hidden to the executing program; important examples are the programmable graphical computing model that provides heap, stack-based operations, shared memory, and multi-threaded concurrency. Although it is possible to imagine a Just In Time compiler that maps programs for the virtual machines to the underlying architecture, the program will not contain enough information to efficiently bridge the gap between computational paradigms that may differ signifficantly. In this PhD work we want to investigate general approaches to bridge this gap, by providing suitable programming abstractions not affecting the general structure of the virtual machine, but consent control over the particular underlying architecture.