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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Petaflops router

Disclosed is a method and system for performing operations on at least one input data vector in order to produce at least one output vector to permit easy, scalable and fast programming of a petascale equivalent supercomputer. A PetaFlops Router may comprise one or more PetaFlops Nodes, which may be connected to each other and/or external data provider/consumers via a programmable crossbar switch external to the PetaFlops Node. Each PetaFlops Node has a FPGA and a programmable intra-FPGA crossbar switch that permits input and output variables to be configurably connected to various physical operators contained in the FPGA as desired by a user. This allows a user to specify the instruction set of the system on a per-application basis. Further, the intra-FPGA crossbar switch permits the output of one operation to be delivered as an input to a second operation. By configuring the external crossbar switch, the output of a first operation on a first PetaFlops Node may be used as the input for a second operation on a second PetaFlops Node. An embodiment may provide an ability for the system to recognize and generate pipelined functions. Streaming operators may be connected together at run-time and appropriately staged to allow data to flow through a series of functions. This allows the system to provide high throughput and parallelism when possible. The PetaFlops Router may implement the user desired instructions by appropriately configuring the intra-FPGA crossbar switch on each PetaFlops Node and the external crossbar switch.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1998

A Petaflops Era Computing Analysis

This report covers a study of the potential for petaflops (1O(exp 15) floating point operations per second) computing. This study was performed within the year 1996 and should be considered as the first step in an on-going effort. 'Me analysis concludes that a petaflop system is technically feasible but not feasible with today's state-of-the-art. Since the computer arena is now a commodity business, most experts expect that a petaflops system will evolve from current technology in an evolutionary fashion. To meet the price expectations of users waiting for petaflop performance, great improvements in lowering component costs will be required. Lower power consumption is also a must. The present rate of progress in improved performance places the date of introduction of petaflop systems at about 2010. Several years before that date, it is projected that the resolution limit of chips will reach the now known resolution limit. Aside from the economic problems and constraints, software is identified as the major problem. The tone of this initial study is more pessimistic than most of the Super-published material available on petaflop systems. Workers in the field are expected to generate more data which could serve to provide a basis for a more informed projection. This report includes an annotated bibliography.

Preston, Frank S.↗
NASA NTRS2000

HTMT-class Latency Tolerant Parallel Architecture for Petaflops Scale Computation

Computational Aero Sciences and other numeric intensive computation disciplines demand computing throughputs substantially greater than the Teraflops scale systems only now becoming available. The related fields of fluids, structures, thermal, combustion, and dynamic controls are among the interdisciplinary areas that in combination with sufficient resolution and advanced adaptive techniques may force performance requirements towards Petaflops. This will be especially true for compute intensive models such as Navier-Stokes are or when such system models are only part of a larger design optimization computation involving many design points. Yet recent experience with conventional MPP configurations comprising commodity processing and memory components has shown that larger scale frequently results in higher programming difficulty and lower system efficiency. While important advances in system software and algorithms techniques have had some impact on efficiency and programmability for certain classes of problems, in general it is unlikely that software alone will resolve the challenges to higher scalability. As in the past, future generations of high-end computers may require a combination of hardware architecture and system software advances to enable efficient operation at a Petaflops level. The NASA led HTMT project has engaged the talents of a broad interdisciplinary team to develop a new strategy in high-end system architecture to deliver petaflops scale computing in the 2004/5 timeframe. The Hybrid-Technology, MultiThreaded parallel computer architecture incorporates several advanced technologies in combination with an innovative dynamic adaptive scheduling mechanism to provide unprecedented performance and efficiency within practical constraints of cost, complexity, and power consumption. The emerging superconductor Rapid Single Flux Quantum electronics can operate at 100 GHz (the record is 770 GHz) and one percent of the power required by convention semiconductor logic. Wave Division Multiplexing optical communications can approach a peak per fiber bandwidth of 1 Tbps and the new Data Vortex network topology employing this technology can connect tens of thousands of ports providing a bi-section bandwidth on the order of a Petabyte per second with latencies well below 100 nanoseconds, even under heavy loads. Processor-in-Memory (PIM) technology combines logic and memory on the same chip exposing the internal bandwidth of the memory row buffers at low latency. And holographic storage photorefractive storage technologies provide high-density memory with access a thousand times faster than conventional disk technologies. Together these technologies enable a new class of shared memory system architecture with a peak performance in the range of a Petaflops but size and power requirements comparable to today's largest Teraflops scale systems. To achieve high-sustained performance, HTMT combines an advanced multithreading processor architecture with a memory-driven coarse-grained latency management strategy called "percolation", yielding high efficiency while reducing the much of the parallel programming burden. This paper will present the basic system architecture characteristics made possible through this series of advanced technologies and then give a detailed description of the new percolation approach to runtime latency management.

Sterling, Thomas↗
NASA NTRS1997

Onward to Petaflops Computing

With the recent demonstration of a computing rate of one Tflop/s at Sandia National Lab, one might ask what lies ahead for high-end computing. The next major milestone is a sustained rate of one Pflop/s (also written one petaflops, or 10(exp 15) floating-point operations per second). It should be emphasized that we could just as well use the term "peta-ops", since it appears that large scientific systems will be required to perform intensive integer and logical computation in addition to floating-point operations, and completely non- floating-point applications are likely to be important as well. In addition to prodigiously high computational performance, such systems must of necessity feature very large main memories, between ten Tbyte (10(exp 13) byte) and one Pbyte (10 (exp 15) byte) depending on application, as well as commensurate I/O bandwidth and huge mass storage facilities. The current consensus of scientists who have performed initial studies in this field is that "affordable" petaflops systems may be feasible by the year 2010, assuming that certain key technologies continue to progress at current rates. A sustained petaflops computing capability however is a daunting challenge; it appears significantly more challenging from today's state-of-the-art than achieving one Tflop/s has been from the level of one Gflop/s about 12 years ago. Challenges are faced in the arena of device technology, system architecture, system software, algorithms and applications. This talk will give an overview of some of these challenges, and describe some of the recent initiatives to address them.

Bailey, David H.↗
DOE OSTI2013

20 petaflops simulation of proteins suspensions in crowding conditions, In: SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis

We present performance results for the simulation of proteins suspensions in crowding conditions obtained with MUPHY, a computational platform for multi-scale simulations of real-life biofluidic problems. Previous versions of MUPHY have been used in the past for the simulation of blood flow through the human coronary arteries and DNA translocation across nanopores. The simulation exhibits excellent scalability up to 18, 000 K20X Nvidia GPUs and achieves almost 20 Petaflops of aggregate sustained performance with a peak performance of 27.5 Petaflops for the most intensive computing component. Those figures demonstrate once again the flexibility of MUPHY in simulating biofluidic phenomena, exploiting at their best the features of the architecture in use. Preliminary results were obtained in the present case on a completely different platform, the IBM Blue Gene/Q. The combination of novel mathematical models, computational algorithms, hardware technology, code tuning and parallelization techniques required to achieve these results are presented.

Computer Science↗
DOE OSTI2013

Mira: Argonne's 10-petaflops supercomputer

Mira, Argonne's petascale IBM Blue Gene/Q system, ushers in a new era of scientific supercomputing at the Argonne Leadership Computing Facility. An engineering marvel, the 10-petaflops supercomputer is capable of carrying out 10 quadrillion calculations per second. As a machine for open science, any researcher with a question that requires large-scale computing resources can submit a proposal for time on Mira, typically in allocations of millions of core-hours, to run programs for their experiments. This adds up to billions of hours of computing time per year.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

PAMOP Project: Petaflop Computations in Support of Experiments.

Our computation effort is primarily concentrated in support of current and future measurements being carried out at various synchrotron radiation facilities around the globe and for charge transfer experiments. In our work we solve the Schrödinger or Dirac equation for the appropriate collision problem using the R-matrix or R-matrix with pseudo-states approach from first principles. The time dependent lattice (TDL) method is also used in our work on charge exchange. A brief summary of the methodology and ongoing developments implemented in the R-matrix suite of Breit-Pauli and Dirac-Atomic R-matrix codes (DARC) is presented. We illustrate vividly the sophistication level of large scale petaflop computations necessary to model accurately the spectra currently being measured at various synchrotron radiation facilities. The new Cray XC40 architecture installed at HLRS is playing a vital role in our computational effort.

Advance Light Source↗
NASA NTRS1997

Petaflops Computing: The Key Algorithmic Challenges

The prospect of petaflops-class computers brings to the fore some important algorithmic issues that have been considered in the high performance computing community for several years. Key among them are (1) concurrency (whether the fundamental concurrency of an algorithm is sufficient to keep thousands of processors productively busy); (2) data locality; (3) latency tolerance; and (4) memory and operation count scaling. This introductory presentation will give an overview of these issues.

Bailey, David H.↗
NASA NTRS2002

Gilgamesh: A Multithreaded Processor-In-Memory Architecture for Petaflops Computing

Processor-in-Memory (PIM) architectures avoid the von Neumann bottleneck in conventional machines by integrating high-density DRAM and CMOS logic on the same chip. Parallel systems based on this new technology are expected to provide higher scalability, adaptability, robustness, fault tolerance and lower power consumption than current MPPs or commodity clusters. In this paper we describe the design of Gilgamesh, a PIM-based massively parallel architecture, and elements of its execution model. Gilgamesh extends existing PIM capabilities by incorporating advanced mechanisms for virtualizing tasks and data and providing adaptive resource management for load balancing and latency tolerance. The Gilgamesh execution model is based on macroservers, a middleware layer which supports object-based runtime management of data and threads allowing explicit and dynamic control of locality and load balancing. The paper concludes with a discussion of related research activities and an outlook to future work.

management locality load balance↗
DOE OSTI2019

Direct simulation Monte Carlo on petaflop supercomputers and beyond

The gold-standard definition of the Direct Simulation Monte Carlo (DSMC) method is given in the 1994 book by Bird [Molecular Gas Dynamics and the Direct Simulation of Gas Flows (Clarendon Press, Oxford, UK, 1994)], which refined his pioneering earlier papers in which he first formulated the method. In the intervening 25 years, DSMC has become the method of choice for modeling rarefied gas dynamics in a variety of scenarios. The chief concern to applying DSMC to more dense or even continuum flows is its computational expense compared to continuum computational fluid dynamics methods. The dramatic (nearly billion-fold) increase in speed of the largest supercomputers over the last 30 years has thus been a key enabling factor in using DSMC to model a richer variety of flows, due to the method’s inherent parallelism. We have developed the open-source SPARTA DSMC code with the goal of running DSMC efficiently on the largest machines, both current and future. It is largely an implementation of Bird’s 1994 formulation. In this work, we describe algorithms used in SPARTA to enable DSMC to operate in parallel at the scale of many billions of particles or grid cells, or with billions of surface elements. We highlight a few examples of the kinds of fundamental physics questions and engineering applications that DSMC can address at these scales.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Designing a graphics processing unit accelerated petaflop capable lattice Boltzmann solver: Read aligned data layouts and asynchronous communication

The lattice Boltzmann method is a well-established numerical approach for complex fluid flow simulations. Recently, general-purpose graphics processing units (GPUs) have become available as high-performance computing resources at large scale. We report on designing and implementing a lattice Boltzmann solver for multi-GPU systems that achieves 1.79 PFLOPS performance on 16,384 GPUs. To achieve this performance, we introduce a GPU compatible version of the so-called bundle data layout and eliminate the halo sites in order to improve data access alignment. Furthermore, we make use of the possibility to overlap data transfer between the host central processing unit and the device GPU with computing on the GPU. As a benchmark case, we simulate flow in porous media and measure both strong and weak scaling performance with the emphasis being on large-scale simulations using realistic input data.

Computer Science↗
NASA NTRS1996

Processor-In-Memory (PIM) Based Architectures for PetaFlops Potential Massively Parallel Processing

The report summarizes the work performed at the University of Notre Dame under a NASA grant from July 15, 1995 through July 14, 1996. Researchers involved in the work included the PI, Dr. Peter M. Kogge, and three graduate students under his direction in the Computer Science and Engineering Department: Stephen Dartt, Costin Iancu, and Lakshmi Narayanaswany. The organization of this report is as follows. Section 2 is a summary of the problem addressed by this work. Section 3 is a summary of the project's objectives and approach. Section 4 summarizes PIM technology briefly. Section 5 overviews the main results of the work. Section 6 then discusses the importance of the results and future directions. Also attached to this report are copies of several technical reports and publications whose contents directly reflect results developed during this study.

Kogge, Peter M.↗
NASA NTRS1999

Virtual Petaflop Simulation: Parallel Potential Solvers and New Integrators for Gravitational Systems

"The orbit of any one planet depends on the combined motion of all the planets, not to mention the actions of all these on each other. To consider simultaneously all these causes of motion and to define these motions by exact laws allowing of convenient calculation exceeds, unless I am mistaken, the forces of the entire human intellect" -Isaac Newton 1687. Epochal surveys are throwing down the gauntlet for cosmological simulation. We describe three keys to meeting the challenge of N-body simulation: adaptive potential solvers, adaptive integrators and volume renormalization. With these techniques and a dedicated Teraflop facility, simulation can stay even with observation of the Universe. We also describe some problems in the formation and stability of planetary systems. Here, the challenge is to perform accurate integrations that retain Hamiltonian properties for 10(exp 13) timesteps.

Lake, George↗
NASA NTRS1997

Onward to Petaflops Computing

With programs such as the US High Performance Computing and Communications Program (HPCCP), the attention of scientists and engineers worldwide has been focused on the potential of very high performance scientific computing, namely systems that are hundreds or thousands of times more powerful than those typically available in desktop systems at any given point in time. Extending the frontiers of computing in this manner has resulted in remarkable advances, both in computing technology itself and also in the various scientific and engineering disciplines that utilize these systems. Within the month or two, a sustained rate of 1 Tflop/s (also written 1 teraflops, or 10(exp 12) floating-point operations per second) is likely to be achieved by the 'ASCI Red' system at Sandia National Laboratory in New Mexico. With this objective in sight, it is reasonable to ask what lies ahead for high-end computing.

Bailey, David H.↗
NASA NTRS1999

The Feasibility of Adaptive Unstructured Computations On Petaflops Systems

This viewgraph presentation covers the advantages of mesh adaptation, unstructured grids, and dynamic load balancing. It illustrates parallel adaptive communications, and explains PLUM (Parallel dynamic load balancing for adaptive unstructured meshes), and PSAW (Proper Self Avoiding Walks).

Biswas, Rupak↗