A Virtualized Self-Adaptive Parallel Programming Framework for Heterogeneous High Productivity Computers

This paper proposed a virtualized self-adaptive heterogeneous high productivity computers parallel programming framework (VAPPF), which is composed of virtualization-based runtime system (VRTS) and virtualized adaptive parallel programming model (VAPPM). Virtualization-based runtime system is composed of node-level virtual machine monitor (NVMM) and system-level virtual infrastructure (SVI). VAPPM program model is not only compatible with conventional data parallel, but also support task parallel. Moreover, with the concept of domains and virtualized process locale, virtualization-based runtime system can map between computation and processors according to system-level resources view and performance model. By conceal the hardware details through both runtime system level and programming model level by virtualization, the framework provides programmers a middle-level view independent of hardware details. Programmers can do their programming and debugging works on this middle-level view, and then, the runtime system map it into specific hardware environment. By this way, programming can be relatively separated from specific hardware architectures, this model realized an efficient work division between programmers and systems, and can help to improve the systempsilas programmability, scalability, portability, robustness, performance, and productivity.