Custom Integrated Circuits

Contains table of contents for Part III, table of contents for Section 1 and reports on eleven research projects.IBM CorporationMIT School of EngineeringNational Science Foundation Grant MIP 94-23221Defense Advanced Research Projects Agency/U.S. Army Intelligence Center Contract DABT63-94-C-0053Mitsubishi CorporationNational Science Foundation Young Investigator Award Fellowship MIP 92-58376Joint Industry Program on Offshore Structure AnalysisAnalog DevicesDefense Advanced Research Projects AgencyCadence Design SystemsMAFET ConsortiumConsortium for Superconducting ElectronicsNational Defense Science and Engineering Graduate FellowshipDigital Equipment CorporationMIT Lincoln LaboratorySemiconductor Research CorporationMultiuniversity Research IntiativeNational Science Foundatio

Thermo-Mechanical Reliability and Electrical Performance of Indium Interconnects and Under Bump Metallization

This thesis presents reliability analysis of indium interconnects and Under Bump Metallization (UBM) in flip chip devices. Flip chip assemblies with the use of bump interconnections are frequently used, especially in high density, three-dimensional electronic devices. Currently there are many methods for interconnect bumping, all of which require UBM. The UBM is required for interconnection, diffusion resistance and quality electrical contact between substrate and device. Bonded silicon test vehicles were comprised of Indium bumps and three UBM compositions: Ti/Ni/Au (200\xc5/1000\xc5/500\xc5), Ti/Ni (200\xc5/1000\xc5), Ni (1000\xc5). UBM and indium were deposited by evaporation and exposed to unbiased accelerated temperature cycling(-55°C to 125°C, 15°C/min ramp rate). Finite Element Analysis (FEA) simulations were used to gain understanding of non-linear strain behavior of indium interconnects during temperature cycling. Experimental testing coupled with FEA simulations facilitated cycle-to-failure calculations. FEA results show plastic strain concentrations within indium bump below failure limits. It has been demonstrated that fabrication of Ti/Ni/Au, Ti/Ni, and Ni UBM stacks performed reliably within infant mortality failure region

2020 NASA Technology Taxonomy

This document is an update (new photos used) of the PDF version of the 2020 NASA Technology Taxonomy that will be available to download on the OCT Public Website. The updated 2020 NASA Technology Taxonomy, or "technology dictionary", uses a technology discipline based approach that realigns like-technologies independent of their application within the NASA mission portfolio. This tool is meant to serve as a common technology discipline-based communication tool across the agency and with its partners in other government agencies, academia, industry, and across the world

Simulation Intelligence: Towards a New Generation of Scientific Methods

The original "Seven Motifs" set forth a roadmap of essential methods for the field of scientific computing, where a motif is an algorithmic method that captures a pattern of computation and data movement. We present the "Nine Motifs of Simulation Intelligence", a roadmap for the development and integration of the essential algorithms necessary for a merger of scientific computing, scientific simulation, and artificial intelligence. We call this merger simulation intelligence (SI), for short. We argue the motifs of simulation intelligence are interconnected and interdependent, much like the components within the layers of an operating system. Using this metaphor, we explore the nature of each layer of the simulation intelligence operating system stack (SI-stack) and the motifs therein: (1) Multi-physics and multi-scale modeling; (2) Surrogate modeling and emulation; (3) Simulation-based inference; (4) Causal modeling and inference; (5) Agent-based modeling; (6) Probabilistic programming; (7) Differentiable programming; (8) Open-ended optimization; (9) Machine programming. We believe coordinated efforts between motifs offers immense opportunity to accelerate scientific discovery, from solving inverse problems in synthetic biology and climate science, to directing nuclear energy experiments and predicting emergent behavior in socioeconomic settings. We elaborate on each layer of the SI-stack, detailing the state-of-art methods, presenting examples to highlight challenges and opportunities, and advocating for specific ways to advance the motifs and the synergies from their combinations. Advancing and integrating these technologies can enable a robust and efficient hypothesis-simulation-analysis type of scientific method, which we introduce with several use-cases for human-machine teaming and automated science

NASA Technology Plan 1998

This NASA Strategic Plan describes an ambitious, exciting vision for the Agency across all its Strategic Enterprises that addresses a series of fundamental questions of science and research. This vision is so challenging that it literally depends on the success of an aggressive, cutting-edge advanced technology development program. The objective of this plan is to describe the NASA-wide technology program in a manner that provides not only the content of ongoing and planned activities, but also the rationale and justification for these activities in the context of NASA's future needs. The scope of this plan is Agencywide, and it includes technology investments to support all major space and aeronautics program areas, but particular emphasis is placed on longer term strategic technology efforts that will have broad impact across the spectrum of NASA activities and perhaps beyond. Our goal is to broaden the understanding of NASA technology programs and to encourage greater participation from outside the Agency. By relating technology goals to anticipated mission needs, we hope to stimulate additional innovative approaches to technology challenges and promote more cooperative programs with partners outside NASA who share common goals. We also believe that this will increase the transfer of NASA-sponsored technology into nonaerospace applications, resulting in an even greater return on the investment in NASA

CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences

This report documents the results of a study to address the long range, strategic planning required by NASA's Revolutionary Computational Aerosciences (RCA) program in the area of computational fluid dynamics (CFD), including future software and hardware requirements for High Performance Computing (HPC). Specifically, the "Vision 2030" CFD study is to provide a knowledge-based forecast of the future computational capabilities required for turbulent, transitional, and reacting flow simulations across a broad Mach number regime, and to lay the foundation for the development of a future framework and/or environment where physics-based, accurate predictions of complex turbulent flows, including flow separation, can be accomplished routinely and efficiently in cooperation with other physics-based simulations to enable multi-physics analysis and design. Specific technical requirements from the aerospace industrial and scientific communities were obtained to determine critical capability gaps, anticipated technical challenges, and impediments to achieving the target CFD capability in 2030. A preliminary development plan and roadmap were created to help focus investments in technology development to help achieve the CFD vision in 2030

Automated Synthesis of Memristor Crossbar Networks

The advancement of semiconductor device technology over the past decades has enabled the design of increasingly complex electrical and computational machines. Electronic design automation (EDA) has played a significant role in the design and implementation of transistor-based machines. However, as transistors move closer toward their physical limits, the speed-up provided by Moore\u27s law will grind to a halt. Once again, we find ourselves on the verge of a paradigm shift in the computational sciences as newer devices pave the way for novel approaches to computing. One of such devices is the memristor -- a resistor with non-volatile memory. Memristors can be used as junctional switches in crossbar circuits, which comprise of intersecting sets of vertical and horizontal nanowires. The major contribution of this dissertation lies in automating the design of such crossbar circuits -- doing a new kind of EDA for a new kind of computational machinery. In general, this dissertation attempts to answer the following questions: a. How can we synthesize crossbars for computing large Boolean formulas, up to 128-bit? b. How can we synthesize more compact crossbars for small Boolean formulas, up to 8-bit? c. For a given loop-free C program doing integer arithmetic, is it possible to synthesize an equivalent crossbar circuit? We have presented novel solutions to each of the above problems. Our new, proposed solutions resolve a number of significant bottlenecks in existing research, via the usage of innovative logic representation and artificial intelligence techniques. For large Boolean formulas (up to 128-bit), we have utilized Reduced Ordered Binary Decision Diagrams (ROBDDs) to automatically synthesize linearly growing crossbar circuits that compute them. This cutting edge approach towards flow-based computing has yielded state-of-the-art results. It is worth noting that this approach is scalable to n-bit Boolean formulas. We have made significant original contributions by leveraging artificial intelligence for automatic synthesis of compact crossbar circuits. This inventive method has been expanded to encompass crossbar networks with 1D1M (1-diode-1-memristor) switches, as well. The resultant circuits satisfy the tight constraints of the Feynman Grand Prize challenge and are able to perform 8-bit binary addition. A leading edge development for end-to-end computation with flow-based crossbars has been implemented, which involves methodical translation of loop-free C programs into crossbar circuits via automated synthesis. The original contributions described in this dissertation reflect the substantial progress we have made in the area of electronic design automation for synthesis of memristor crossbar networks