The impact of Moore's Law and loss of Dennard scaling: Are DSP SoCs an energy efficient alternative to x86 SoCs?

As advanced packaging application space evolves and continues to deviate from the conventional shrinkage pathway predicted by Moore's law, material suppliers need to continue to work with OEMs, OSATs and Foundries to identify specific opportunities. One such opportunity continues to present itself in developing new materials to support new platforms for next generation products to support 3D chip stacking and TSV applications. The newer material sets can be established to meet more challenging design requirements associated with the demands, presented by the application from both a physical/lithographical processing and design perspective. Next generation packages requires the development of new dielectric materials that can support both the physical demands of 3D chip stacking and TSV package design aspects while maintaining strengths of the existing material platform. While vertical integration necessitates the use of thinned substrates and its associated integration challenges, there is a continuing need to support horizontal shrinkage typical of the Moore's Law, which pushes the lithography envelope requiring finer pitch and smaller feature resolution capability. This presentation identifies the strategy we have taken and highlights approach taking in the development of low temperature curable photoimageable dielectric materials with enhanced lithographic performance. We will discuss the methodology used to create benzocyclobutene based dielectric material curable at 180 °C and show how lithographic performance can be tuned to allow sub 5 micron via using broad band illumination. Finally we will review the impact of low temperature processing on the mechanical, thermal and electrical properties of this novel photoimageable dielectric material.

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Towards a Thermal Moore’s Law

Advances in Electronic Packaging, Parts A, B, and C ◽

10.1115/ipack2005-73409 ◽

2005 ◽

Cited By ~ 5

Author(s):

Shankar Krishnan ◽

Suresh V. Garimella ◽

Greg M. Chrysler ◽

Ravi V. Mahajan

Keyword(s):

Heat Sink ◽

High Efficiency ◽

Thermal Design ◽

Air Cooling ◽

Thermoelectric Coolers ◽

Moore’S Law ◽

Moore's Law ◽

The Impact ◽

Power Densities ◽

Design Power

The thermal design power trends and power densities for present and future microprocessors are investigated. The trends are derived based on Moore’s law and scaling theory. Both active and stand-by power are discussed and accounted for in the calculations. A brief discussion of various leakage power components and their impact on the power density trends is provided. Two different lower limits of heat dissipation for irreversible logic computers are discussed. These are based on the irreversibility of logic to represent one bit of information, and on the distribution of electrons to represent a bit. These limits are found to be two or more orders of magnitude lower than present-day microprocessor thermal design power trends. Further, these trends are compared to the projected trends for the desktop product sector from the International Technology Roadmap for Semiconductors (ITRS). To evaluate the thermal impact of the projected power densities, heat sink thermal resistances are calculated for a given technology target. Based on the heat sink thermal resistance trends, the evolution of an air-cooling limit consistent with Moore’s law is predicted. One viable alternative to air-cooling, i.e., the use of high-efficiency solid-state thermoelectric coolers (TECs), is explored. The impact of different parasitics on the thermoelectric figure of merit (ZT) is quantified. This paper was also originally published as part of the Proceedings of the ASME 2005 Heat Transfer Summer Conference.

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Near-Threshold Computing: Reclaiming Moore's Law Through Energy Efficient Integrated Circuits

Proceedings of the IEEE ◽

10.1109/jproc.2009.2034764 ◽

2010 ◽

Vol 98 (2) ◽

pp. 253-266 ◽

Cited By ~ 490

Author(s):

Ronald G. Dreslinski ◽

Michael Wieckowski ◽

David Blaauw ◽

Dennis Sylvester ◽

Trevor Mudge

Keyword(s):

Integrated Circuits ◽

Energy Efficient ◽

Moore’S Law ◽

Moore's Law ◽

Near Threshold

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Beyond Moore’s technologies: operation principles of a superconductor alternative

Beilstein Journal of Nanotechnology ◽

10.3762/bjnano.8.269 ◽

2017 ◽

Vol 8 ◽

pp. 2689-2710 ◽

Cited By ~ 62

Author(s):

Igor I Soloviev ◽

Nikolay V Klenov ◽

Sergey V Bakurskiy ◽

Mikhail Yu Kupriyanov ◽

Alexander L Gudkov ◽

...

Keyword(s):

Energy Efficiency ◽

High Performance Computing ◽

Retrospective Review ◽

Digital Technology ◽

Energy Efficient ◽

High Performance ◽

Moore’S Law ◽

Moore's Law ◽

Memory Circuits ◽

Performance Computing

The predictions of Moore’s law are considered by experts to be valid until 2020 giving rise to “post-Moore’s” technologies afterwards. Energy efficiency is one of the major challenges in high-performance computing that should be answered. Superconductor digital technology is a promising post-Moore’s alternative for the development of supercomputers. In this paper, we consider operation principles of an energy-efficient superconductor logic and memory circuits with a short retrospective review of their evolution. We analyze their shortcomings in respect to computer circuits design. Possible ways of further research are outlined.

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AI, native supercomputing and the revival of Moore's Law

APSIPA Transactions on Signal and Information Processing ◽

10.1017/atsip.2017.9 ◽

2017 ◽

Vol 6 ◽

Cited By ~ 1

Author(s):

Chien-Ping Lu

Keyword(s):

Digital Computer ◽

Energy Efficient ◽

Instruction Set ◽

Moore’S Law ◽

Moore's Law ◽

Domain Specific ◽

Alan Turing ◽

Computing Machinery ◽

Learning Software ◽

Save Energy

Artificial Intelligence (AI) was the inspiration that shaped computing as we know it today. In this article, I explore why and how AI would continue to inspire computing and reinvent it when Moore's Law is running out of steam. At the dawn of computing, Alan Turing proposed that instead of comprising many different specific machines, the computing machinery for AI should be a Universal Digital Computer, modeled after human computers, which carry out calculations with pencil on paper. Based on the belief that a digital computer would be significantly faster, more diligent and patient than a human, he anticipated that AI would be advanced as software. In modern terminology, a universal computer would be designed to understand a language known as an Instruction Set Architecture (ISA), and software would be translated into the ISA. Since then, universal computers have become exponentially faster and more energy efficient through Moore's Law, while software has grown more sophisticated. Even though software has not yet made a machine think, it has been changing how we live fundamentally. The computing revolution started when the software was decoupled from the computing machinery. Since the slowdown of Moore's Law in 2005, the universal computer is no longer improving exponentially in terms of speed and energy efficiency. It has to carry ISA legacy, and cannot be aggressively modified to save energy. Turing's proposition of AI as software is challenged, and the temptation of making many domain-specific AI machines emerges. Thanks to Deep Learning, software can stay decoupled from the computing machinery in the language of linear algebra, which it has in common with supercomputing. A new universal computer for AI understands such language natively to then become a Native Supercomputer. AI has been and will still be the inspiration for computing. The quest to make machines think continues amid the slowdown of Moore's Law. AI might not only maximize the remaining benefits of Moore's Law, but also revive Moore's Law beyond current technology.

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