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At least 757 records · Page 42

NANDFlashSim: High-Fidelity, Microarchitecture-Aware NAND Flash Memory Simulation [NANDFlashSim: Intrinsic Latency Variation Aware NAND Flash Memory System Modeling and Simulation at Microarchitecture Level]

As the popularity of NAND flash expands in arenas from embedded systems to high-performance computing, a high-fidelity understanding of its specific properties becomes increasingly important. Further, with the increasing trend toward multiple-die, multiple-plane architectures and high-speed interfaces, flash memory systems are expected to continue to scale and cheapen, resulting in their broader proliferation. However, when designing NAND-based devices, making decisions about the optimal system configuration is nontrivial, because flash is sensitive to a number of parameters and suffers from inherent latency variations, and no available tools suffice for studying these nuances. The parameters include the architectures, such as multidie and multiplane, diverse node technologies, bit densities, and cell reliabilities. Therefore, we introduce NANDFlashSim, a high-fidelity, latency-variation-aware, and highly configurable NAND-flash simulator, which implements a detailed timing model for 16 state-of-the-art NAND operations. Using NANDFlashSim, we notably discover the following. First, regardless of the operation, reads fail to leverage internal parallelism. Second, MLC provides lower I/O bus contention than SLC, but contention becomes a serious problem as the number of dies increases. Third, many-die architectures outperform many-plane architectures for disk-friendly workloads. Lastly, employing a high-performance I/O bus or an increased page size does not enhance energy savings.

97 MATHEMATICS AND COMPUTING↗

Runtime Systems for Energy Efficiency in Advanced Computing Systems

As heterogeneous systems become increasingly popular for both mobile and high-performance computing, conventional efficiency techniques such as dynamic voltage and frequency scaling (DVFS) fail to account for the tightly coupled and varied nature of systems on a chip (SoCs). In this work, we explore the impact of system unaware DVFS techniques on a mobile SoC under three benchmark suites: Chai, Rodinia, and Antutu. We then analyze performance trends across the suites to identify a set of consistent operating points that optimally balance power and performance across the system. The consistent operating points are then constructed into a dependency graph which can be leveraged to produce a more effective, SoC-wide governor.

97 MATHEMATICS AND COMPUTING↗

On the Hilbert-Huang Transform Data Processing System Development

One of the main heritage tools used in scientific and engineering data spectrum analysis is the Fourier Integral Transform and its high performance digital equivalent - the Fast Fourier Transform (FFT). The Fourier view of nonlinear mechanics that had existed for a long time, and the associated FFT (fairly recent development), carry strong a-priori assumptions about the source data, such as linearity and of being stationary. Natural phenomena measurements are essentially nonlinear and nonstationary. A very recent development at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), known as the Hilbert-Huang Transform (HHT) proposes a novel approach to the solution for the nonlinear class of spectrum analysis problems. Using the Empirical Mode Decomposition (EMD) followed by the Hilbert Transform of the empirical decomposition data (HT), the HHT allows spectrum analysis of nonlinear and nonstationary data by using an engineering a-posteriori data processing, based on the EMD algorithm. This results in a non-constrained decomposition of a source real value data vector into a finite set of Intrinsic Mode Functions (IMF) that can be further analyzed for spectrum interpretation by the classical Hilbert Transform. This paper describes phase one of the development of a new engineering tool, the HHT Data Processing System (HHTDPS). The HHTDPS allows applying the "T to a data vector in a fashion similar to the heritage FFT. It is a generic, low cost, high performance personal computer (PC) based system that implements the HHT computational algorithms in a user friendly, file driven environment. This paper also presents a quantitative analysis for a complex waveform data sample, a summary of technology commercialization efforts and the lessons learned from this new technology development.

Kizhner, Semion↗

Data Movement Dominates: Final Report

Over the past three years in this project, what we have observed is that the primary reason for data movement in large-scale systems is that the per-node capacity is not large enough—i.e., one of the solutions to the data-movement problem (certainly not the only solution that is required, but a significant one nonetheless) is to increase per-node capacity so that inter-node traffic is reduced. This unfortunately is not as simple as it sounds. Today’s main memory systems for datacenters, enterprise computing systems, and supercomputers, fail to provide high per-socket capacity [Dirik & Jacob 2009; Cooper-Balis et al. 2012], except at extremely high price points (factors of 10–100x the cost/bit of consumer main-memory systems) [Stokes 2008]. The reason is that our choice of technology for today’s main memory systems—i.e., DRAM, which we have used as a main-memory technology since the 1970s [Jacob et al. 2007]—can no longer keep up with our needs for density and price per bit. Main memory systems have always been built from the cheapest, densest, lowest-power memory technology available, and DRAM is no longer the cheapest, the densest, nor the lowest-power storage technology out there. It is now time for DRAM to go the way that SRAM went: move out of the way for a cheaper, slower, denser storage technology, and become a cache instead. This inflection point has happened before, in the context of SRAM yielding to DRAM. There was once a time that SRAM was the storage technology of choice for all main memories [Tomasulo 1967; Thornton 1970; Kidder 1981]. However, once DRAM hit volume production in the 1970s and 80s, it supplanted SRAM as a main memory technology because it was cheaper, and it was denser. It also happened to be lower power, but that was not the primary consideration of the day. At the time, it was recognized that DRAM was much slower than SRAM, but it was only at the supercomputer level (For instance the Cray X-MP in the 1980s and its follow-on, the Cray Y-MP, in the 1990s) that could one afford to build ever- larger main memories out of SRAM—the reasoning for moving to DRAM was that an appropriately designed memory hierarchy, built of DRAM as main memory and SRAM as a cache, would approach the performance of SRAM, at the price-per-bit of DRAM [Mashey 1999]. Today it is quite clear that, were one to build an entire multi-gigabyte main memory out of SRAM instead of DRAM, one could improve the performance of almost any computer system by up to an order of magnitude—but this option is not even considered, because to build that system would be prohibitively expensive. It is now time to revisit the same design choice in the context of modern technologies and modern systems. For reasons both technical and economic, we can no longer afford to build ever-larger main memory systems out of DRAM. Flash memory, on the other hand, is significantly cheaper and denser than DRAM and therefore should take its place. While it is true that flash is significantly slower than DRAM, one can afford to build much larger main memories out of flash than out of DRAM, and we show that an appropriately designed memory hierarchy, built of flash as main memory and DRAM as a cache, will approach the performance of DRAM, at the price-per-bit of flash. In our studies as part of this project, we have investigated Non-Volatile Main Memory (NVMM), a new main-memory architecture for large-scale computing systems, one that is specifically designed to address the weaknesses described previously. In particular, it provides the following features: non-volatility: The bulk of the storage is comprised of NAND flash, and in this organization DRAM is used only as a cache, not as main memory. Furthermore, the flash is journaled, which means that operations such as checkpoint/restore are already built into the system. 1+ terabytes of storage per socket: SSDs and DRAM DIMMs have roughly the same form factor (several square inches of PCB surface area), and terabyte SSDs are now commonplace. performance approaching that of DRAM: DRAM is used as a cache to the flash system. price-per-bit approaching that of NAND: Flash is currently well under $0.50 per gigabyte; DDR3 SDRAM is currently just over $10 per gigabyte [Newegg 2014]. Even today, one can build an easily affordable main memory system with a terabyte or more of NAND storage per CPU socket (which would be extremely expensive were one to use DRAM), and our cycle- accurate, full-system experiments show that this can be done at a performance point that lies within a factor of two of DRAM.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Results of data base management system parameterized performance testing related to GSFC scientific applications

The results of a variety of tests designed to demonstrate and evaluate the performance of several commercially available data base management system (DBMS) products compatible with the Digital Equipment Corporation VAX 11/780 computer system are summarized. The tests were performed on the INGRES, ORACLE, and SEED DBMS products employing applications that were similar to scientific applications under development by NASA. The objectives of this testing included determining the strength and weaknesses of the candidate systems, performance trade-offs of various design alternatives and the impact of some installation and environmental (computer related) influences.

Carchedi, C. H.↗

C++ Resource Intelligent Compilation for GPU Enabled Applications

We are nearing the limits of Moore's Law with current computing technology. As industries push for more performance from smaller systems, alternate methods of computation such as Graphics Processing Units (GPUs) should be considered. Many of these systems utilize the Compute Unified Device Architecture (CUDA) to give programmers access to individual compute elements of the GPU for general purpose computing tasks. Direct access to the GPU's parallel multi-core architecture enables highly efficient computation and can drastically reduce the time required for complex algorithms or data analysis. Of course not all systems have a CUDA-enabled device to leverage, and so applications must consider optional support for users with these devices. Resource Intelligent Compilation (RIC) addresses this situation by enabling GPU-based acceleration of existing applications without affecting users without GPUs. Resource Intelligent Compilation (RIC) creates C/C++ modules that can be compiled to create a standard CPU version or GPU accelerated version of a program, depending on hardware availability. This is accomplished through a toolbox of programming strategies based on features of the CUDA API. Using this toolbox, existing applications can be modified with ease to support GPU acceleration, and new applications can be generated with just a few simple modifications. All of this culminates in an accelerated application for users with the appropriate hardware, with no performance impact to standard systems. This memorandum presents all the important features involved in supporting and implementing RIC and an example of using RIC to accelerate an existing mathematical model, without removing support for standard users. Through this memorandum, NASA engineers can acquire a set of guidelines to follow for RIC-compliant development, seamlessly accelerating C/C++ applications.

GPU↗

High-speed, automatic controller design considerations for integrating array processor, multi-microprocessor, and host computer system architectures

Modern control systems must typically perform real-time identification and control, as well as coordinate a host of other activities related to user interaction, online graphics, and file management. This paper discusses five global design considerations which are useful to integrate array processor, multimicroprocessor, and host computer system architectures into versatile, high-speed controllers. Such controllers are capable of very high control throughput, and can maintain constant interaction with the nonreal-time or user environment. As an application example, the architecture of a high-speed, closed-loop controller used to actively control helicopter vibration is briefly discussed. Although this system has been designed for use as the controller for real-time rotorcraft dynamics and control studies in a wind tunnel environment, the controller architecture can generally be applied to a wide range of automatic control applications.

Jacklin, S. A.↗

Active control of buckling of flexible beams

Mathematical models are presented that simulate the dynamic characteristics of shape memory alloy actuators made of nickel-titanium alloy (Nitinol) controlling the buckling of compressive structural members. A closed-loop computer-controlled system has been designed, based on the proposed mathematical models, and has been implemented to control the buckling of simple beams. The performance of the computer-controlled system is evaluated experimentally and compared with the theoretical predictions to validate the developed models. The results emphasized the importance of buckling control and suggest the potential of shape memory alloy actuators as attractive means for controlling structural deformation in a simple and reliable way.

Baz, A.↗

Efficient Memory Access with NumPy Global Arrays using Local Memory Access

This paper discusses the work completed working with Global Arrays of data on distributed multi-computer systems and improving their performance. The tasks completed were done at Pacific Northwest National Laboratory in the Science Undergrad Laboratory Internship program in the summer of 2013 for the Data Intensive Computing Group in the Fundamental and Computational Sciences DIrectorate. This work was done on the Global Arrays Toolkit developed by this group. This toolkit is an interface for programmers to more easily create arrays of data on networks of computers. This is useful because scientific computation is often done on large amounts of data sometimes so large that individual computers cannot hold all of it. This data is held in array form and can best be processed on supercomputers which often consist of a network of individual computers doing their computation in parallel. One major challenge for this sort of programming is that operations on arrays on multiple computers is very complex and an interface is needed so that these arrays seem like they are on a single computer. This is what global arrays does. The work done here is to use more efficient operations on that data that requires less copying of data to be completed. This saves a lot of time because copying data on many different computers is time intensive. The way this challenge was solved is when data to be operated on with binary operations are on the same computer, they are not copied when they are accessed. When they are on separate computers, only one set is copied when accessed. This saves time because of less copying done although more data access operations were done.

Daily, Jeffrey A.↗

Simulation studies of the GOES-I Image Navigation and Registration (INR) system

The GOES-I Image Navigation and Registration (INR) system will fly on the next generation of NOAA geostationary meteorological satellites. This system uses observations of stars and earth landmarks made by the Imager and Sounder Instruments themselves to determine the orbit, attitude, and misalignment state of the spacecraft and instruments. An extensive program of simulation and analysis has been conducted to assess the expected performance of the INR system. This paper discusses these activities and presents some computer simulation results showing expected system performance under a variety of conditions including station-keeping.

Carr, James L.↗

Flight test of takeoff performance monitoring system

The Takeoff Performance Monitoring System (TOPMS) is a computer software and hardware graphics system that visually displays current runway position, acceleration performance, engine status, and other situation advisory information to aid pilots in their decision to continue or to abort a takeoff. The system was developed at the Langley Research Center using the fixed-base Transport Systems Research Vehicle (TSRV) simulator. (The TSRV is a highly modified Boeing 737-100 research airplane.) Several versions of the TOPMS displays were evaluated on the TSRV B-737 simulator by more than 40 research, United States Air Force, airline and industry and pilots who rated the system satisfactory and recommended further development and testing. In this study, the TOPMS was flight tested on the TSRV. A total of 55 takeoff and 30 abort situations were investigated at 5 airfields. TOPMS displays were observed on the navigation display screen in the TSRV research flight deck during various nominal and off-nominal situations, including normal takeoffs; reduced-throttle takeoffs; induced-acceleration deficiencies; simulated-engine failures; and several gross-weight, runway-geometry, runway-surface, and ambient conditions. All tests were performed on dry runways. The TOPMS software executed accurately during the flight tests and the displays correctly depicted the various test conditions. Evaluation pilots found the displays easy to monitor and understand. The algorithm provides pretakeoff predictions of the nominal distances that are needed to accelerate the airplane to takeoff speed and to brake it to a stop; these predictions agreed reasonably well with corresponding values measured during several fully executed and aborted takeoffs. The TOPMS is operational and has been retained on the TSRV for general use and demonstration.

Middleton, David B.↗

The Archive Solution for Distributed Workflow Management Agents of the CMS Experiment at LHC

The CMS experiment at the CERN LHC developed the Workflow Management Archive system to persistently store unstructured framework job report documents produced by distributed workflow management agents. In this paper we present its architecture, implementation, deployment, and integration with the CMS and CERN computing infrastructures, such as central HDFS and Hadoop Spark cluster. The system leverages modern technologies such as a document oriented database and the Hadoop eco-system to provide the necessary flexibility to reliably process, store, and aggregate $\mathcal{O}$(1M) documents on a daily basis. We describe the data transformation, the short and long term storage layers, the query language, along with the aggregation pipeline developed to visualize various performance metrics to assist CMS data operators in assessing the performance of the CMS computing system.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

CI/CD Efforts for Validation, Verification and Benchmarking OpenMP Implementations

Software developers must adapt to keep up with the changing capabilities of platforms so that they can utilize the power of High-Performance Computers (HPC), including exascale systems. OpenMP, a directive-based parallel programming model, allows developers to include directives to existing C, C++, or Fortran code to allow node level parallelism without compromising performance. This paper describes our CI/CD efforts to provide easy evaluation of the support of OpenMP across different compilers using existing testsuites and benchmark suites on HPC platforms. Our main contributions include (1) the set of a Continuous Integration (CI) and Continuous Development (CD) workflow that captures bugs and provides faster feedback to compiler developers, (2) an evaluation of OpenMP (offloading) implementations supported by AMD, HPE, GNU, LLVM, and Intel, and (3) evaluation of the quality of compilers across different heterogeneous HPC platforms. With the comprehensive testing through the CI/CD workflow, we aim to provide a comprehensive understanding of the current state of OpenMP (offloading) support in different compilers and heterogeneous platforms consisting of CPUs and GPUs from NVIDIA, AMD, and Intel.

Jarmusch, Aaron↗

Data Point Averaging for Computational Fluid Dynamics Data

A system and method for generating fluid flow parameter data for use in aerodynamic heating analysis. Computational fluid dynamics data is generated for a number of points in an area on a surface to be analyzed. Sub-areas corresponding to areas of the surface for which an aerodynamic heating analysis is to be performed are identified. A computer system automatically determines a sub-set of the number of points corresponding to each of the number of sub-areas and determines a value for each of the number of sub-areas using the data for the sub-set of points corresponding to each of the number of sub-areas. The value is determined as an average of the data for the sub-set of points corresponding to each of the number of sub-areas. The resulting parameter values then may be used to perform an aerodynamic heating analysis.

Norman, David, Jr.↗

Data Point Averaging for Computational Fluid Dynamics Data

A system and method for generating fluid flow parameter data for use in aerodynamic heating analysis. Computational fluid dynamics data is generated for a number of points in an area on a surface to be analyzed. Sub-areas corresponding to areas of the surface for which an aerodynamic heating analysis is to be performed are identified. A computer system automatically determines a sub-set of the number of points corresponding to each of the number of sub-areas and determines a value for each of the number of sub-areas using the data for the sub-set of points corresponding to each of the number of sub-areas. The value is determined as an average of the data for the sub-set of points corresponding to each of the number of sub-areas. The resulting parameter values then may be used to perform an aerodynamic heating analysis.

Norman, Jr., David↗

Demonstrating integration of CBP and ASCEM simulation tools - 15627

DOE-EM is supporting two crosscutting projects to develop software and conduct targeted experiments to enhance performance and risk assessment capabilities: the Cementitious Barriers Partnership (CBP) and the Advanced Simulation Capability for Environmental Management (ASCEM). The CBP is a smaller-scale project of coordinated software development and experimentation focused on cementitious materials. ASCEM is a larger-scale project aimed at developing next-generation, science-based, reactive flow and transport simulation capabilities and supporting modeling tool-sets within a high-performance computing framework to address DOE-EM's waste management and environmental cleanup challenges. Complementary integration of CBP and ASCEM software tool-sets has been demonstrated through a joint simulation of radionuclide release and transport in a representative tank closure scenario. Specialized CBP capabilities for simulating reactive transport in cementitious materials were utilized in a near-field simulation of radionuclide leaching from the engineered system. The high-performance computing (HPC) capabilities of the ASCEM Amanzi simulator were utilized to simulate far-field flow and transport in the natural environment outside the closed tank. The ASCEM flow simulation provided boundary conditions to the CBP near-field model, which in turn provided radionuclide source terms to the ASCEM far-field transport simulation. The joint demonstration illustrates how the two crosscutting projects can be used in a complementary manner to enhance DOE performance and risk assessment. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Scalable domain decomposition solvers for stochastic PDEs in high performance computing

Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolution in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ESnet-JLab FPGA Accelerated Transport (data plane) [EJFAT (udplb)] v1.0

The ESnet-JLab FPGA Accelerated Transport system is a solution for streaming high-speed scientific measurement data from Data Acquisition Systems (DAQs) to high-performance computing facilties. It is generally compatible with many science workflows, and makes no assumptions about the specifics of any particular experiment. This program (udplb) implements the data plane portion of the EJFAT system. It is an FPGA design that rewrites and forwards data packets from a UDP-based scientific workflow to high-performance compute nodes. It depends on another program (udplbd, disclosed separately) to implement the control system.

Bengough, Peter [Malleable Networks, Inc.]↗