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Experimental Evaluation and Workload Characterization for High-Performance Computer Architectures

This research is conducted in the context of the Joint NSF/NASA Initiative on Evaluation (JNNIE). JNNIE is an inter-agency research program that goes beyond typical.bencbking to provide and in-depth evaluations and understanding of the factors that limit the scalability of high-performance computing systems. Many NSF and NASA centers have participated in the effort. Our research effort was an integral part of implementing JNNIE in the NASA ESS grand challenge applications context. Our research work under this program was composed of three distinct, but related activities. They include the evaluation of NASA ESS high- performance computing testbeds using the wavelet decomposition application; evaluation of NASA ESS testbeds using astrophysical simulation applications; and developing an experimental model for workload characterization for understanding workload requirements. In this report, we provide a summary of findings that covers all three parts, a list of the publications that resulted from this effort, and three appendices with the details of each of the studies using a key publication developed under the respective work.

El-Ghazawi, Tarek A.

Information Power Grid: Distributed High-Performance Computing and Large-Scale Data Management for Science and Engineering

The term "Grid" refers to distributed, high performance computing and data handling infrastructure that incorporates geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. The vision for NASN's Information Power Grid - a computing and data Grid - is that it will provide significant new capabilities to scientists and engineers by facilitating routine construction of information based problem solving environments / frameworks that will knit together widely distributed computing, data, instrument, and human resources into just-in-time systems that can address complex and large-scale computing and data analysis problems. IPG development and deployment is addressing requirements obtained by analyzing a number of different application areas, in particular from the NASA Aero-Space Technology Enterprise. This analysis has focussed primarily on two types of users: The scientist / design engineer whose primary interest is problem solving (e.g., determining wing aerodynamic characteristics in many different operating environments), and whose primary interface to IPG will be through various sorts of problem solving frameworks. The second type of user if the tool designer: The computational scientists who convert physics and mathematics into code that can simulate the physical world. These are the two primary users of IPG, and they have rather different requirements. This paper describes the current state of IPG (the operational testbed), the set of capabilities being put into place for the operational prototype IPG, as well as some of the longer term R&D tasks.

Johnston, William E.

Information Power Grid: Distributed High-Performance Computing and Large-Scale Data Management for Science and Engineering

We use the term "Grid" to refer to distributed, high performance computing and data handling infrastructure that incorporates geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. This infrastructure includes: (1) Tools for constructing collaborative, application oriented Problem Solving Environments / Frameworks (the primary user interfaces for Grids); (2) Programming environments, tools, and services providing various approaches for building applications that use aggregated computing and storage resources, and federated data sources; (3) Comprehensive and consistent set of location independent tools and services for accessing and managing dynamic collections of widely distributed resources: heterogeneous computing systems, storage systems, real-time data sources and instruments, human collaborators, and communications systems; (4) Operational infrastructure including management tools for distributed systems and distributed resources, user services, accounting and auditing, strong and location independent user authentication and authorization, and overall system security services The vision for NASA's Information Power Grid - a computing and data Grid - is that it will provide significant new capabilities to scientists and engineers by facilitating routine construction of information based problem solving environments / frameworks. Such Grids will knit together widely distributed computing, data, instrument, and human resources into just-in-time systems that can address complex and large-scale computing and data analysis problems. Examples of these problems include: (1) Coupled, multidisciplinary simulations too large for single systems (e.g., multi-component NPSS turbomachine simulation); (2) Use of widely distributed, federated data archives (e.g., simultaneous access to metrological, topological, aircraft performance, and flight path scheduling databases supporting a National Air Space Simulation systems}; (3) Coupling large-scale computing and data systems to scientific and engineering instruments (e.g., realtime interaction with experiments through real-time data analysis and interpretation presented to the experimentalist in ways that allow direct interaction with the experiment (instead of just with instrument control); (5) Highly interactive, augmented reality and virtual reality remote collaborations (e.g., Ames / Boeing Remote Help Desk providing field maintenance use of coupled video and NDI to a remote, on-line airframe structures expert who uses this data to index into detailed design databases, and returns 3D internal aircraft geometry to the field); (5) Single computational problems too large for any single system (e.g. the rotocraft reference calculation). Grids also have the potential to provide pools of resources that could be called on in extraordinary / rapid response situations (such as disaster response) because they can provide common interfaces and access mechanisms, standardized management, and uniform user authentication and authorization, for large collections of distributed resources (whether or not they normally function in concert). IPG development and deployment is addressing requirements obtained by analyzing a number of different application areas, in particular from the NASA Aero-Space Technology Enterprise. This analysis has focussed primarily on two types of users: the scientist / design engineer whose primary interest is problem solving (e.g. determining wing aerodynamic characteristics in many different operating environments), and whose primary interface to IPG will be through various sorts of problem solving frameworks. The second type of user is the tool designer: the computational scientists who convert physics and mathematics into code that can simulate the physical world. These are the two primary users of IPG, and they have rather different requirements. The results of the analysis of the needs of these two types of users provides a broad set of requirements that gives rise to a general set of required capabilities. The IPG project is intended to address all of these requirements. In some cases the required computing technology exists, and in some cases it must be researched and developed. The project is using available technology to provide a prototype set of capabilities in a persistent distributed computing testbed. Beyond this, there are required capabilities that are not immediately available, and whose development spans the range from near-term engineering development (one to two years) to much longer term R&D (three to six years). Additional information is contained in the original.

Johnston, William E.

Requirements for multidisciplinary design of aerospace vehicles on high performance computers

The design of aerospace vehicles is becoming increasingly complex as the various contributing disciplines and physical components become more tightly coupled. This coupling leads to computational problems that will be tractable only if significant advances in high performance computing systems are made. Some of the modeling, algorithmic and software requirements generated by the design problem are discussed.

Voigt, Robert G.

High-Performance Computing and Four-Dimensional Data Assimilation: The Impact on Future and Current Problems

This is the final technical report for the project entitled: "High-Performance Computing and Four-Dimensional Data Assimilation: The Impact on Future and Current Problems", funded at NPAC by the DAO at NASA/GSFC. First, the motivation for the project is given in the introductory section, followed by the executive summary of major accomplishments and the list of project-related publications. Detailed analysis and description of research results is given in subsequent chapters and in the Appendix.

Makivic, Miloje S.

Implementation of the Lanczos eigen-solver for the CSI code on high performance computers

The focus of this research is to implement a Lanczos algorithm for the Control-Structure Integration (CSI) code which can exploit both parallel and vector capabilities provided by modern, high performance computers. A partial restoring orthogonality scheme is also developed and incorporated into the basic Lanczos algorithm. The numerical performance of the proposed parallel-vector Lanczos algorithm is demonstrated by solving for the frequencies and mode shapes of the Phase Zero CSI model. The superior performance of the Lanczos algorithm is illustrated in tabular form.

Nguyen, Duc T.

A High Performance Computing Approach to Tree Cover Delineation in 1-m NAIP Imagery Using a Probabilistic Learning Framework

Tree cover delineation is a useful instrument in deriving Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) airborne imagery data. Numerous algorithms have been designed to address this problem, but most of them do not scale to these datasets, which are of the order of terabytes. In this paper, we present a semi-automated probabilistic framework for the segmentation and classification of 1-m National Agriculture Imagery Program (NAIP) for tree-cover delineation for the whole of Continental United States, using a High Performance Computing Architecture. Classification is performed using a multi-layer Feedforward Backpropagation Neural Network and segmentation is performed using a Statistical Region Merging algorithm. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field, which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by relabeling misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the whole state of California, spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles. The framework produced true positive rates of around 88% for fragmented forests and 74% for urban tree cover areas, with false positive rates lower than 2% for both landscapes. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR canopy height model (CHM) showed the effectiveness of our framework for generating accurate high-resolution tree-cover maps.

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Parallel-vector unsymmetric Eigen-Solver on high performance computers

The popular QR algorithm for solving all eigenvalues of an unsymmetric matrix is reviewed. Among the basic components in the QR algorithm, it was concluded from this study, that the reduction of an unsymmetric matrix to a Hessenberg form (before applying the QR algorithm itself) can be done effectively by exploiting the vector speed and multiple processors offered by modern high-performance computers. Numerical examples of several test cases have indicated that the proposed parallel-vector algorithm for converting a given unsymmetric matrix to a Hessenberg form offers computational advantages over the existing algorithm. The time saving obtained by the proposed methods is increased as the problem size increased.

Nguyen, Duc T.

A vector unsymmetric eigenequation solver for nonlinear flutter analysis on high-performance computers

A finite element approach is presented for determining the nonlinear flutter characteristics of composite panels using unsteady, third-order piston theory aerodynamics. Both nonlinear structural (large-amplitude) and nonlinear aerodynamics terms are considered in the finite element formulation. Solution procedures are presented to solve the nonlinear panel flutter and the large-amplitude free vibration finite element equations. Nonlinear aerodynamic and linear structural finite element flutter results for composite panels are also presented. An efficient, vector-version generalized unsymmetric eigenequation solver is developed for large-amplitude vibration and nonlinear panel flutter analyses on high-performance computers.

Qin, Jiangning

High performance computing applications in neurobiological research

The human nervous system is a massively parallel processor of information. The vast numbers of neurons, synapses and circuits is daunting to those seeking to understand the neural basis of consciousness and intellect. Pervading obstacles are lack of knowledge of the detailed, three-dimensional (3-D) organization of even a simple neural system and the paucity of large scale, biologically relevant computer simulations. We use high performance graphics workstations and supercomputers to study the 3-D organization of gravity sensors as a prototype architecture foreshadowing more complex systems. Scaled-down simulations run on a Silicon Graphics workstation and scale-up, three-dimensional versions run on the Cray Y-MP and CM5 supercomputers.

Ross, Muriel D.

Multidisciplinary Design Optimization of a Full Vehicle with High Performance Computing

Multidisciplinary design optimization (MDO) of a full vehicle under the constraints of crashworthiness, NVH (Noise, Vibration and Harshness), durability, and other performance attributes is one of the imperative goals for automotive industry. However, it is often infeasible due to the lack of computational resources, robust simulation capabilities, and efficient optimization methodologies. This paper intends to move closer towards that goal by using parallel computers for the intensive computation and combining different approximations for dissimilar analyses in the MDO process. The MDO process presented in this paper is an extension of the previous work reported by Sobieski et al. In addition to the roof crush, two full vehicle crash modes are added: full frontal impact and 50% frontal offset crash. Instead of using an adaptive polynomial response surface method, this paper employs a DOE/RSM method for exploring the design space and constructing highly nonlinear crash functions. Two NMO strategies are used and results are compared. This paper demonstrates that with high performance computing, a conventionally intractable real world full vehicle multidisciplinary optimization problem considering all performance attributes with large number of design variables become feasible.

Yang, R. J.

RISC Processors and High Performance Computing

In this tutorial, we will discuss top five current RISC microprocessors: The IBM Power2, which is used in the IBM RS6000/590 workstation and in the IBM SP2 parallel supercomputer, the DEC Alpha, which is in the DEC Alpha workstation and in the Cray T3D; the MIPS R8000, which is used in the SGI Power Challenge; the HP PA-RISC 7100, which is used in the HP 700 series workstations and in the Convex Exemplar; and the Cray proprietary processor, which is used in the new Cray J916. The architecture of these microprocessors will first be presented. The effective performance of these processors will then be compared, both by citing standard benchmarks and also in the context of implementing a real applications. In the process, different programming models such as data parallel (CM Fortran and HPF) and message passing (PVM and MPI) will be introduced and compared. The latest NAS Parallel Benchmark (NPB) absolute performance and performance per dollar figures will be presented. The next generation of the NP13 will also be described. The tutorial will conclude with a discussion of general trends in the field of high performance computing, including likely future developments in hardware and software technology, and the relative roles of vector supercomputers tightly coupled parallel computers, and clusters of workstations. This tutorial will provide a unique cross-machine comparison not available elsewhere.

Saini, Subhash

Image Processor Electronics (IPE): The High-Performance Computing System for NASA SWIFT Mission

Gamma Ray Bursts (GRBs) are believed to be the most powerful explosions that have occurred in the Universe since the Big Bang and are a mystery to the scientific community. Swift, a NASA mission that includes international participation, was designed and built in preparation for a 2003 launch to help to determine the origin of Gamma Ray Bursts. Locating the position in the sky where a burst originates requires intensive computing, because the duration of a GRB can range between a few milliseconds up to approximately a minute. The instrument data system must constantly accept multiple images representing large regions of the sky that are generated by sixteen gamma ray detectors operating in parallel. It then must process the received images very quickly in order to determine the existence of possible gamma ray bursts and their locations. The high-performance instrument data computing system that accomplishes this is called the Image Processor Electronics (IPE). The IPE was designed, built and tested by NASA Goddard Space Flight Center (GSFC) in order to meet these challenging requirements. The IPE is a small size, low power and high performing computing system for space applications. This paper addresses the system implementation and the system hardware architecture of the IPE. The paper concludes with the IPE system performance that was measured during end-to-end system testing.

Nguyen, Quang H.

Portability Support for High Performance Computing

While a large number of tools have been developed to support application portability, high performance application developers often prefer to use vendor-provided, non-portable programming interfaces. This phenomena indicates the mismatch between user priorities and tool capabilities. This paper summarizes the results of a user survey and a developer survey. The user survey has revealed the user priorities and resulted in three criteria for evaluating tool support for portability. The developer survey has resulted in the evaluation of portability support and indicated the possibilities and difficulties of improvements.

Cheng, Doreen Y.

Investigating the Mobility of Light Autonomous Tracked Vehicles using a High Performance Computing Simulation Capability

This paper is concerned with the physics-based simulation of light tracked vehicles operating on rough deformable terrain. The focus is on small autonomous vehicles, which weigh less than 100 lb and move on deformable and rough terrain that is feature rich and no longer representable using a continuum approach. A scenario of interest is, for instance, the simulation of a reconnaissance mission for a high mobility lightweight robot where objects such as a boulder or a ditch that could otherwise be considered small for a truck or tank, become major obstacles that can impede the mobility of the light autonomous vehicle and negatively impact the success of its mission. Analyzing and gauging the mobility and performance of these light vehicles is accomplished through a modeling and simulation capability called Chrono::Engine. Chrono::Engine relies on parallel execution on Graphics Processing Unit (GPU) cards.

tracked vehicles

High-Performance Computing for the Electromagnetic Modeling and Simulation of Interconnects

The electromagnetic modeling of packages and interconnects plays a very important role in the design of high-speed digital circuits, and is most efficiently performed by using computer-aided design algorithms. In recent years, packaging has become a critical area in the design of high-speed communication systems and fast computers, and the importance of the software support for their development has increased accordingly. Throughout this project, our efforts have focused on the development of modeling and simulation techniques and algorithms that permit the fast computation of the electrical parameters of interconnects and the efficient simulation of their electrical performance.

Schutt-Aine, Jose E.

Client/Server data serving for high performance computing

This paper will attempt to examine the industry requirements for shared network data storage and sustained high speed (10's to 100's to thousands of megabytes per second) network data serving via the NFS and FTP protocol suite. It will discuss the current structural and architectural impediments to achieving these sorts of data rates cost effectively today on many general purpose servers and will describe and architecture and resulting product family that addresses these problems. The sustained performance levels that were achieved in the lab will be shown as well as a discussion of early customer experiences utilizing both the HIPPI-IP and ATM OC3-IP network interfaces.

Wood, Chris

Full custom VLSI - A technology for high performance computing

Full custom VLSI is presented as a viable technology for addressing the need for the computing capabilities required for the real-time health monitoring of spacecraft systems. This technology presents solutions that cannot be realized with stored program computers or semicustom VLSI; also, it is not dependent on current IC processes. It is argued that, while design time is longer, full custom VLSI produces the fastest and densest VLSI solution and that high density normally also yields low manufacturing costs.

Maki, Gary K.