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Chien, Andrew A.

Publications and source records attributed to Chien, Andrew A..

7 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Reimagining Codesign for Advanced Scientific Computing: Report for the ASCR Workshop on Reimagining Codesign

In March 2021, the U.S. Department of Energy’s Advanced Scientific Computing Research program convened the Workshop on Reimagining Codesign. The workshop, also known as ReCoDe, was organized around discussions on eight topic areas: (1) codesign for traditional high-performance computing workloads; (2) codesign of memory/storage systems; (3) codesign of machine learning, neuromorphic, quantum, and other non-von Neumann accelerators; (4) codesign for edge computing and processing at experimental instruments; (5) codesign for security and privacy; (6) hardware design tools and open-source hardware for high-productivity codesign; (7) tools, software stack, and programming languages for high-productivity codesign; and (8) quantitative tools and data collection for modeling and simulation for codesign. The panels identified four Priority Research Directions from these deliberations: (1) breakthrough computing capabilities with targeted heterogeneity and rapid design; (2) software and applications that embrace radical architecture diversity; (3) engineered security and integrity, from transistors to applications; and (4) design with data-rich processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Position Papers for the ASCR Workshop on Reimagining Codesign

On behalf of the Advanced Scientific Computing Research (ASCR) program in the US Department of Energy (DOE) Office of Science, we are organizing a Workshop on Reimagining Codesign (ReCoDe). Codesign is the process of jointly designing interoperating components of a computing system—in particular: applications, algorithms, system software, programming models, and the hardware on which they run. The goal is to maximize the overall performance, efficiency, and other desirable qualities of the system as a whole. Codesign is a standard methodology in the embedded-systems community, where space, power, and cost constraints are commonly pitted against execution speed for a tightly constrained feature set. Over the last decade, the DOE has invested in codesign efforts to foster the development of exascale computing systems for broad classes of scientific and engineering applications. The ReCoDe workshop hopes to explore how scientific applications of interest to the DOE can be accelerated through close interactions with hardware designers and software-stack developers, in which all components adapt to each other’s requirements and constraints. We want to answer the question of what are the key tools and methodologies for accomplishing codesign in today’s computing landscape, and what will be the highest impact targets for meeting DOE’s emerging mission requirements. This workshop aims to bring together DOE, industry, and academia to identify opportunities to build on past codesign successes and identify new areas that are either emerging or that may need reimagining for the future. We want to continue to find opportunities that can be pursued as a joint effort and continue to break down the traditional customer/vendor dichotomy with true partnerships. From this work, DOE will benefit from increased application performance relative to what stock hardware or existing general-purpose roadmaps can provide, and vendors will benefit from expanding their hardware’s capabilities to address needs they might have not otherwise anticipated and thereby create more widespread interest in their products. The workshop will be structured around a set of breakout sessions, with every attendee expected to participate actively in the discussions. Afterward, workshop attendees—from DOE, industry, and academia—will produce a report for ASCR that summarizes the findings made during the workshop.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Large-Scale and Extreme-Scale Computing with Stranded Green Power: Opportunities and Costs

Power consumption and associated carbon emissions are increasingly critical challenges for large-scale computing. Recent research proposes exploiting stranded power-uneconomic renewable power-for green supercomputing in a system called Zero-Carbon Cloud (ZCCloud). These efforts studied production supercomputing workloads on stranded-power based computing resources, demonstrating their achievable productivity. We explore economic viability of stranded-power based supercomputing, using three datacenter total-cost-of-ownership (TOO) models to study cost-effectiveness. These studies show that ZCCloud's approach can be cost-effective in the USA today, and is even more attractive in regions with higher power prices (e.g., Japan, Germany), achieving cost advantages as large as 50 percent. Environmental and power-grid benefits are a further advantage. We also explore the sensitivity of these results to changes in hardware TOO; cheaper hardware or longer lifetimes magnify the attractiveness of stranded-power based approaches, yielding advantages as large as 91 percent. These results are robust across different TCO models. Lastly, we study extreme-scale supercomputers ( >100 MW), finding stranded-power can increase peak capability per cost by as much as 80 percent.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Exploring versioned distributed arrays for resilience in scientific applications: Global view resilience

Exascale studies project reliability challenges for future HPC systems. We present the Global View Resilience (GVR) system, a library for portable resilience. GVR begins with a subset of the Global Arrays interface, and adds new capabilities to create versions, name versions, and compute on version data. Applications can focus versioning where and when it is most productive, and customize for each application structure independently. This control is portable, and its embedding in application source makes it natural to express and easy to maintain. The ability to name multiple versions and “partially materialize” them efficiently makes ambitious forward-recovery based on “data slices” across versions or data structures both easy to express and efficient. Using several large applications (OpenMC, preconditioned conjugate gradient (PCG) solver, ddcMD, and Chombo), we evaluate the programming effort to add resilience. The required changes are small (< 2% lines of code (LOC)), localized and machine-independent, and perhaps most important, require no software architecture changes. We also measure the overhead of adding GVR versioning and show that overheads < 2% are generally achieved. This overhead suggests that GVR can be implemented in large-scale codes and support portable error recovery with modest investment and runtime impact. Our results are drawn from both IBM BG/Q and Cray XC30 experiments, demonstrating portability. We also present two case studies of flexible error recovery, illustrating how GVR can be used for multi-version rollback recovery, and several different forward-recovery schemes. GVR’s multi-version enables applications to survive latent errors (silent data corruption) with significant detection latency, and forward recovery can make that recovery extremely efficient. Lastly, our results suggest that GVR is scalable, portable, and efficient. GVR interfaces are flexible, supporting a variety of recovery schemes, and altogether GVR embodies a gentle-slope path to tolerate growing error rates in future extreme-scale systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Data centers as dispatchable loads to harness stranded power

Here, we analyze how traditional data center placement and optimal placement of dispatchable data centers affect power grid efficiency. We use detailed network models, stochastic optimization formulations, and diverse renewable generation scenarios to perform our analysis. Our results reveal that significant spillage and stranded power will persist in power grids as wind power levels are increased. A counter-intuitive finding is that collocating data centers with inflexible loads next to wind farms has limited impacts on renewable portfolio standard (RPS) goals because it provides limited system-level flexibility. Such an approach can, in fact, increase stranded power and fossil-fueled generation. In contrast, optimally placing data centers that are dispatchable provides system-wide flexibility, reduces stranded power, and improves efficiency. In short, optimally placed dispatchable computing loads can enable better scaling to high RPS. In our case study, we find that these dispatchable computing loads are powered to 60-80% of their requested capacity, indicating that there are significant economic incentives provided by stranded power.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

The Concert system - Compiler and runtime technology for efficient concurrent object-oriented programming

Concurrent object-oriented languages, particularly fine-grained approaches, reduce the difficulty of large scale concurrent programming by providing modularity through encapsulation while exposing large degrees of concurrency. Despite these programmability advantages, such languages have historically suffered from poor efficiency. This paper describes the Concert project whose goal is to develop portable, efficient implementations of fine-grained concurrent object-oriented languages. Our approach incorporates aggressive program analysis and program transformation with careful information management at every stage from the compiler to the runtime system. The paper discusses the basic elements of the Concert approach along with a description of the potential payoffs. Initial performance results and specific plans for system development are also detailed.

Chien, Andrew A.↗