An Assessment of the National Institute of Standards and Technology Programs Fiscal Year 1994 (1994) / Chapter Skim
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9 Computing and Applied Mathematics Laboratory
9 Computing and Applied Mathematics Laboratory
Pages 227-246
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Chapter 9 Computing arid Applied Mathematics Laboratory
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Voigt, National Science Foundation Submitted for the pane} by its Chair, Ralph Z Roskies, this assessment of the fiscal year 1994 technical activities of the Computing and Applied Mathematics Laboratory (CAML)
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Proposed NIST expansions assign specific activities to CAM, but it should be noted that, in each case, CAML works in cooperation with another NIST laboratory that bears the primary responsibility. CAML provides services directly to industry and other government agencies in the sense that generic methods, tools, and software provided to meet NIST's needs are immediately applicable to the needs of industry and of researchers in universities and national laboratories.
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· Continually improve NIST computing and communications infrastructure. For example, CAML has requested funds for upgrading NIST's central computing facilities and expanding CAML's support for NIST's clistributed systems.
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Measuring Impact The metrics2 suggested by the Statistical Engineering Division in the CAME publication Description of the 1,aboratory anal Its Operation (CAME, NIST, Gaithersburg, Md., May ~ 994; p.
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also heard strong endorsements from other major laboratory directors for centralized Applied and Computational Mathematics Division and Statistical Engineering Division efforts. The pane!
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For example, the Applied and Computational Mathematics Division did significant work with MSEL on metal solidification modeling, and the computing divisions are working with the Chemical Science and Technology Laboratory (CSTL) and the Physics Laboratory to develop unique parallel-processing applications software.
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DIVISIONAL ASSESSMENTS Statistical Engineering Division Mission The Statistical Engineering Division seeks to catalyze experimentation, enhance research, and improve communication of results by collaborating with, and developing effective statistical methods for, NIST scientists and NIST's collaborators from industry. Strategy The Statistical Engineering Division reaches out to NIST scientists and engineers through regular seminars, tutorials on important statistical concepts and tools, active involvement in the development of new NIST standard reference materials (SRMs)
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To achieve its technical objectives, the Statistical Engineering Division supports NIST measurement services to industry through the certification of SRMs, the assessment of test methods, and the development of calibration services; participates in the planning and analysis of physical experiments; maintains awareness of industry needs by direct contact with industrial customers and collaborators and by presenting workshops based on NIST experience; and seeks out and develops new opportunities where statistical methodology will have maximum input. Resources in fiscal year 1994, the Statistical Engineering Division, Gaithersburg, Maryland, group, has a staff totaling approximately 20 fi~-time equivalents (FTEs)
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The Statistical Engineering Division brings a wealth of statistical expertise to bear on its measurement work, as well as nearly 20 years of experience in statistical graphics (e.g., its DATAPLOT program)
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CAME should charge an interim division chief for the Statistical Engineering Division to aggressively shape the division's fixture in the new ITL.
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"The Statistical Engineering Division's two-fold mission, involving basic research in statistical science and collaboration with other NIST scientists, should be broadened to include extensive and direct collaboration with industry" (p.
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Finally, the division is developing a program with SIAM and NSF (similar to the program in the Statistical Engineering Division) to sponsor faculty members for up to ~ year to work on problems of mutual interest.
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Assessment of Technical Programs The long-standing intensive and fruitful interaction between the Applied and Computational Mathematics Division and MSEL is accelerating. Among current major joint projects are a study of recently developed phase-field models for problems of phase change, an area in which NIST scientists have a history of major contributions; an industrially oriented study of soldering with both theoretical and experimental aspects; an international effort focused on obtaining a better understanding of directional solidification with electrical effects; and projects covering aspects of nolvmers and ferromagnetic materials.
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structure. The Applied and Computational Mathematics Division should continue to emphasize the formulation of a specific team project in mathematics-based product design and manufacturing to integrate the division's ongoing research in several areas, including computational geometry and metrology, mathematical modeling, and computational science.
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Office of the Associate Director for Computing The Office of the Associate Director for Computing provides NTST with central scientific computing services, network and data communication, software, voice communications, administrative computing services, and related scientific and technical support. Four computing divisions are involved: Scientific Computing Environments Division, Computer Services Division.
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The computing divisions have positioned themselves to exploit the hinds available to the NIST laboratories through the HPCC initiative, coordinating one of the three major components of HPCC at NIST, high-performance software ( - S)
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recommends that CAML staffinvestigate the requirements for and plan a network security program. An allocation committee should be created consisting of representative users from across NIST charged with the responsibility of making recommendations for resource allocations based on the technical strength of proposals from the user community.
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To their credit, the computing divisions undertook initiatives in all three of the suggested areas. Work is currently under way with the Physics Laboratory to evaluate the efficiency of using networked workstations operating in parallel as an alternative to the Cray supercomputer on a variety of computationally intensive problems.
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