IPDPS 2019 Technical Program

: In 2001, as early high-speed networks were deployed, George Gilder observed that “when the network is as fast as the computer's internal links, the machine disintegrates across the net into a set of special purpose appliances.” Two decades later, our networks are 1,000 times faster, our appliances are increasingly specialized, and our computer systems are indeed disintegrating. As hardware acceleration overcomes speed-of-light delays, time and space merge into a computing continuum. Familiar questions like “where should I compute,” “for what workloads should I design computers,” and "where should I place my computers” seem to allow for a myriad of new answers that are exhilarating but also daunting. Are there concepts that can help guide us as we design applications and computer systems in a world that is untethered from familiar landmarks like center, cloud, edge? I propose some ideas and report on experiments in coding the continuum. Abstract: Parallel computers have come of age and need parallel software to justify their usefulness. There are two major avenues to get programs to run in parallel: parallelizing compilers and parallel languages and/or libraries. In this talk we present our latest results using both approaches and draw some conclusions about their relative effectiveness and potential. In the first part we introduce the Hybrid Analysis (HA) compiler framework that can seamlessly integrate static and run-time analysis of memory references into a single framework capable of full automatic loop level parallelization. Experimental results on 26 benchmarks show full program speedups superior to those obtained by the Intel Fortran compilers. In the second part of this talk we present the Standard Template Adaptive Parallel Library (STAPL) based approach to parallelizing code. STAPL is a collection of generic data structures and algorithms that provides a high productivity, parallel programming infrastructure analogous to the C++ Standard Template Library (STL). In this talk, we provide an overview of the major STAPL components with particular emphasis on graph algorithms. We then present scalability results of real codes using peta scale machines such as IBM BG/Q and Cray. Finally we present some of our ideas for future work in this area. Abstract: The trends in hardware architecture are paving the road towards Exascale. However, these trends are also increasing the complexity of design and development of the software developer environment that is deployed on modern supercomputers. Moreover, the scale and complexity of high-end systems creates a new set of challenges for application developers. Computational scientists are facing system characteristics that will significantly impact the programmability and scalability of applications. In order to address these issues, software architects need to take a holistic view of the entire system and deliver a high-level programming environment that can help maximize programmability, while not losing sight of performance portability. In this talk, I will discuss the current trends in computer architecture and their implications in application development and will present Cray’s high level parallel programming environment for performance and programmability on current and future supercomputers. I will also discuss some of the challenges and open research problems that need to be addressed in order to build a software developer environment for extreme-scale systems that helps users solve multi-disciplinary and multi-scale problems with high levels of performance, programmability, and scalability.