Brent C. Gorda

Paravirtualization for HPC systems

In this work, we investigate the efficacy of using paravirtualizing software for performance-critical HPC kernels and applications. We present a comprehensive performance evaluation of Xen, a low-overhead, Linux-based, virtual machine monitor, for paravirtualization of HPC cluster systems at LLNL. We investigate subsystem and overall performance using a wide range of benchmarks and applications. We employ statistically sound methods to compare the performance of a paravirtualized kernel against three Linux operating systems: RedHat Enterprise 4 for build versions 2.6.9 and 2.6.12 and the LLNL CHAOS kernel. Our results indicate that Xen is very efficient and practical for HPC systems.

Evaluating the Performance Impact of Xen on MPI and Process Execution For HPC Systems

Virtualization has become increasingly popular for enabling full system isolation, load balancing, and hardware multiplexing for high-end server systems. Virtualizing software has the potential to benefit HPC systems similarly by facilitating efficient cluster management, application isolation, full-system customization, and process migration. However, virtualizing software is not currently employed in HPC environments due to its perceived overhead. In this work, we investigate the overhead imposed by the popular, open-source, Xen virtualization system, on performance-critical HPC kernels and applications. We empirically evaluate the impact of Xen on both communication and computation and compare its use to that of a customized kernel using HPC cluster resources at Lawrence Livermore National Lab (LLNL). We also employ statistically sound methods to compare the performance of a para virtualized kernel against three popular Linux operating systems: RedHat Enterprise 4 (RHEL4) for build versions 2.6.9 and 2.6.12 and the LLNL CHAOS kernel, a specialized version of RHEL4. Our results indicate that Xen is very efficient and practical for HPC systems.

The Parallel C Preprocessor

We describe a parallel extension of the C programming language designed for multiprocessors that provide a facility for sharing memory between processors. The programming model was initially developed on conventional shared memory machines with small processor counts such as the Sequent Balance and Alliant FX/8, but has more recently been used on a scalable massively parallel machine, the BBN TC2000. The programming model is split-join rather than fork-join. Concurrency is exploited to use a fixed number of processors more efficiently rather than to exploit more processors as in the fork-join model. Team splitting, a mechanism to split the team of processors executing a code into subteams to handle parallel subtasks, is used to provide an efficient mechanism to exploit nested concurrency. We have found the split-join programming model to have an inherent implementation advantage, compared to the fork-join model, when the number of processors in a machine becomes large.

A Collaboration and Commercialization Model for Exascale Software Research

We propose a coordinated strategy for exascale software development that includes the incorporation of successful research and development (R&D) into development and engineering (D&E) projects and harvesting the successful D&E projects into products with vendor support (P&S). This allows the most flexible R&D agenda while at the same time providing a commercialization path. This process is described as a natural extension of current focus areas and funding agents for R&D, D&E and P&S, but adds stake holders from the next stage in the process in the upstream processes. This model allows the flexibility to encourage development and competition of ideas in the research, development and productization phases. We anticipate that multiple iterations through this process from R&D through P&S are required to achieve appropriate software for Exascale systems.

BBN TC2000 architecture and programming models

The BBN TC2000 is a scalable general-purpose parallel architecture capable of efficiently supporting both shared memory and message passing programming paradigms. The TC2000 machine architecture and the programming models that have been implemented on it are described. In particular, the split-join model, its memory model, and the message passing model are described. Specifics on how the implementation of these models take advantage of the architecture are included. The synchronization primitives offered in PCP (parallel C processor) and PFP (parallel Fortran preprocessor) are discussed, the debugging and performance monitoring abilities within the models are considered. The time and space scheduling mechanism used on the machine is described.<<ETX>>

The PCP/PFP Programming Models on the BBN TC2000

We describe the PCP/PFP programming models which we are using on the BBN TC2000. The parallel programming models are implemented in a portable manner and will be useful on the scalable shared memory machines we expect to see in the future. We then describe the TC20machine architecture which is a scalable general purpose parallel architecture capable of efficiently supporting both shared memory and message passing programming paradigms. We also briefly describe a PCP implementation of the Gauss elimination algorithm which exploits the large local memories on the TC2000.