Wendy Faulkner, Jacqueline Senker, and LÉa Velho
- Published in print:
- 1995
- Published Online:
- October 2011
- ISBN:
- 9780198288336
- eISBN:
- 9780191684586
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198288336.003.0042
- Subject:
- Business and Management, Information Technology, Knowledge Management
The material for this chapter is based on the findings of two different studies that concern seven US firms and six UK firms that are involved in parallel computing. Since the UK study was conducted ...
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The material for this chapter is based on the findings of two different studies that concern seven US firms and six UK firms that are involved in parallel computing. Since the UK study was conducted during the earlier part of the investigation, the charts used have not been refined to allow for the examination of the impacts and types of STI. As such, related data is instead derived from the US firms. This chapter attempts to look into both the fundamental similarities and differences of these companies. Here, it is realized that PSR plays no small part in the development of technology for parallel computing since this involves government funding and how early users were mostly concerned in government and academic laboratories. This chapter points out, however, that the level of PSR linkage in this field is lower compared to those seen in other fields.Less
The material for this chapter is based on the findings of two different studies that concern seven US firms and six UK firms that are involved in parallel computing. Since the UK study was conducted during the earlier part of the investigation, the charts used have not been refined to allow for the examination of the impacts and types of STI. As such, related data is instead derived from the US firms. This chapter attempts to look into both the fundamental similarities and differences of these companies. Here, it is realized that PSR plays no small part in the development of technology for parallel computing since this involves government funding and how early users were mostly concerned in government and academic laboratories. This chapter points out, however, that the level of PSR linkage in this field is lower compared to those seen in other fields.
Wendy Faulkner and Jacqueline Senker
- Published in print:
- 1995
- Published Online:
- October 2011
- ISBN:
- 9780198288336
- eISBN:
- 9780191684586
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198288336.001.0001
- Subject:
- Business and Management, Information Technology, Knowledge Management
Fostering interaction between industry and academic and government laboratories is widely seen as an important means of facilitating growth and innovation in the technology-based industries. This ...
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Fostering interaction between industry and academic and government laboratories is widely seen as an important means of facilitating growth and innovation in the technology-based industries. This book investigates the research links and knowledge flows between industrial and public sector research in three new and promising fields of advanced technology — biotechnology, engineering ceramics, and parallel computing. Differences between these fields suggest that policies to promote public-private research links should be more effectively targeted. Similarities highlight the general importance to innovation of frontier research in universities, and the need to encourage informal interaction between industrial and public sector researchers.Less
Fostering interaction between industry and academic and government laboratories is widely seen as an important means of facilitating growth and innovation in the technology-based industries. This book investigates the research links and knowledge flows between industrial and public sector research in three new and promising fields of advanced technology — biotechnology, engineering ceramics, and parallel computing. Differences between these fields suggest that policies to promote public-private research links should be more effectively targeted. Similarities highlight the general importance to innovation of frontier research in universities, and the need to encourage informal interaction between industrial and public sector researchers.
Wendy Faulkner, Jacqueline Senker, and LÉa Velho
- Published in print:
- 1995
- Published Online:
- October 2011
- ISBN:
- 9780198288336
- eISBN:
- 9780191684586
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198288336.003.0068
- Subject:
- Business and Management, Information Technology, Knowledge Management
The main aim of this study has been to provide a better understanding of the various processes that both companies and governments have attempted to modify through utilizing policy interventions. ...
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The main aim of this study has been to provide a better understanding of the various processes that both companies and governments have attempted to modify through utilizing policy interventions. Specifically, the book has examined the interaction processes of industrial researchers with government laboratories and academic researchers in order to acquire the necessary knowledge to further innovation. As the study has been proceeded by exploring the differences in technology exhibited by industry-PSR linkages, the book has examined the fields of parallel computing, engineering ceramics, and biotechnology. The book has found that industry-PSR linkages are not without cross-technology diversity, and a taxonomy of factors for these differences has been developed. This concluding chapter provides a summary of the main points of the book and suggestions for future research.Less
The main aim of this study has been to provide a better understanding of the various processes that both companies and governments have attempted to modify through utilizing policy interventions. Specifically, the book has examined the interaction processes of industrial researchers with government laboratories and academic researchers in order to acquire the necessary knowledge to further innovation. As the study has been proceeded by exploring the differences in technology exhibited by industry-PSR linkages, the book has examined the fields of parallel computing, engineering ceramics, and biotechnology. The book has found that industry-PSR linkages are not without cross-technology diversity, and a taxonomy of factors for these differences has been developed. This concluding chapter provides a summary of the main points of the book and suggestions for future research.
Joseph F. Boudreau and Eric S. Swanson
- Published in print:
- 2017
- Published Online:
- February 2018
- ISBN:
- 9780198708636
- eISBN:
- 9780191858598
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780198708636.003.0009
- Subject:
- Physics, Theoretical, Computational, and Statistical Physics
This chapter describes various approaches to concurrency, or “parallel programming”. An overview of high performance computing is followed with a review of Flynn’s taxonomy of parallel computing. ...
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This chapter describes various approaches to concurrency, or “parallel programming”. An overview of high performance computing is followed with a review of Flynn’s taxonomy of parallel computing. Three methods for implementing parallel code using the frameworks provided by MPI, openMP, and C++ threads are presented. The use of the C++ constructs mutex and future to resolve issues of synchronization are discussed. All methods are illustrated with an embarrassingly parallel application to a Monte Carlo integral and common pitfalls are presented. The chapter closes with a discussion and example of the utility of forking processes and the use of C++ sockets and their application in a client/server environment.Less
This chapter describes various approaches to concurrency, or “parallel programming”. An overview of high performance computing is followed with a review of Flynn’s taxonomy of parallel computing. Three methods for implementing parallel code using the frameworks provided by MPI, openMP, and C++ threads are presented. The use of the C++ constructs mutex and future to resolve issues of synchronization are discussed. All methods are illustrated with an embarrassingly parallel application to a Monte Carlo integral and common pitfalls are presented. The chapter closes with a discussion and example of the utility of forking processes and the use of C++ sockets and their application in a client/server environment.
P. Ladevèze, David Néron, and Jean-Charles Passieux
- Published in print:
- 2009
- Published Online:
- February 2010
- ISBN:
- 9780199233854
- eISBN:
- 9780191715532
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199233854.003.0009
- Subject:
- Mathematics, Applied Mathematics
The chapter deals with multiple scales in both space and time. First, the state-of-the-art is presented. Then, we discuss a family of computational approaches using time-space homogenization. ...
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The chapter deals with multiple scales in both space and time. First, the state-of-the-art is presented. Then, we discuss a family of computational approaches using time-space homogenization. Emphasis is put on the time aspects.Less
The chapter deals with multiple scales in both space and time. First, the state-of-the-art is presented. Then, we discuss a family of computational approaches using time-space homogenization. Emphasis is put on the time aspects.
Robin Hanson
- Published in print:
- 2016
- Published Online:
- November 2020
- ISBN:
- 9780198754626
- eISBN:
- 9780191917028
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780198754626.003.0012
- Subject:
- Computer Science, Artificial Intelligence, Machine Learning
Can we say anything about the specific speeds at which ems can run? Because of brain parallelism, the cost of running an em should be nearly proportional ...
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Can we say anything about the specific speeds at which ems can run? Because of brain parallelism, the cost of running an em should be nearly proportional to speed over a wide range of speeds. The upper limit of this proportional-cost em speed range is the “top cheap” speed, that is, the highest speed at which the cost is still nearly proportional to speed. To estimate this speed, we must consider how simulated neurons in em brains might both send faster signals, and more quickly compute what signals to send. Human brain neuron fibers send signals at speeds ranging from 0.5 to 120 meters per second. In contrast, signal speeds in electronic circuit boards today are typically about half the speed of light. If signals in em brains move at electronics speeds, that would be between one million and 300 million times faster than neuron signals. If signal delays are the limiting factor in em brain speed, then this ratio gives an estimate of the maximum speedup possible, at least if em brains have the same spatial size as human brains. proportionally larger speedups are possible if em brains can be made proportionally smaller. Regarding the computation of when to fire a simulated neuron, note that real neurons usually seem to take at least 20 milliseconds to react ( Tovee 1994 ), while even today electronic circuits can switch 10 billion times faster, in one-and-a-half trillionths of a second ( deal et al. 2010 ). A key question is thus: how many electronic circuit cycles does it take to execute a parallel computer program that emulates the firing of a single neuron? For example, if there were an algorithm that could compute a neuron firing in 10 000 of these fastest-known circuit cycles, then an emulation based on this algorithm would run a million times faster than the human brain. As quite complex parallel computer programs can be run in 10 000 cycles, em speedups of at least one million times seem feasible, provided that energy and cooling are cheap enough to profitably allow the use of these fastest electronic circuits. When energy and cooling are more strongly limiting factors, however, the top cheap speed could be slower.
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Can we say anything about the specific speeds at which ems can run? Because of brain parallelism, the cost of running an em should be nearly proportional to speed over a wide range of speeds. The upper limit of this proportional-cost em speed range is the “top cheap” speed, that is, the highest speed at which the cost is still nearly proportional to speed. To estimate this speed, we must consider how simulated neurons in em brains might both send faster signals, and more quickly compute what signals to send. Human brain neuron fibers send signals at speeds ranging from 0.5 to 120 meters per second. In contrast, signal speeds in electronic circuit boards today are typically about half the speed of light. If signals in em brains move at electronics speeds, that would be between one million and 300 million times faster than neuron signals. If signal delays are the limiting factor in em brain speed, then this ratio gives an estimate of the maximum speedup possible, at least if em brains have the same spatial size as human brains. proportionally larger speedups are possible if em brains can be made proportionally smaller. Regarding the computation of when to fire a simulated neuron, note that real neurons usually seem to take at least 20 milliseconds to react ( Tovee 1994 ), while even today electronic circuits can switch 10 billion times faster, in one-and-a-half trillionths of a second ( deal et al. 2010 ). A key question is thus: how many electronic circuit cycles does it take to execute a parallel computer program that emulates the firing of a single neuron? For example, if there were an algorithm that could compute a neuron firing in 10 000 of these fastest-known circuit cycles, then an emulation based on this algorithm would run a million times faster than the human brain. As quite complex parallel computer programs can be run in 10 000 cycles, em speedups of at least one million times seem feasible, provided that energy and cooling are cheap enough to profitably allow the use of these fastest electronic circuits. When energy and cooling are more strongly limiting factors, however, the top cheap speed could be slower.
John Ross, Igor Schreiber, and Marcel O. Vlad
- Published in print:
- 2006
- Published Online:
- November 2020
- ISBN:
- 9780195178685
- eISBN:
- 9780197562277
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780195178685.003.0006
- Subject:
- Chemistry, Physical Chemistry
The topic of this chapter may seem like a digression from methods and approaches to reaction mechanisms, but it is not; it is an introduction to it. We worked on both ...
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The topic of this chapter may seem like a digression from methods and approaches to reaction mechanisms, but it is not; it is an introduction to it. We worked on both topics for some time and there is a basic connection. Think of an electronic device and ask: how are the logic functions of this device determined? Electronic inputs (voltages and currents) are applied and outputs are measured. A truth table is constructed and from this table the logic functions of the device, and at times some of its components, may be inferred. The device is not subjected to the approach toward a chemical mechanism described in the previous chapter, of taking the device apart and testing its simplest components. (That may have to be done sometimes but is to be avoided if possible.) Can such an approach be applicable to chemical systems? We show this to be the case by discussing the implementation of logic and computational devices, both sequential machines such as a universal Turing machine (hand computers, laptops) and parallel machines, by means of macroscopic kinetics; by giving a brief comparison with neural networks; by showing the presence of such devices in chemical and biochemical reaction systems; and by presenting some confirming experiments. The next step is clear: if macroscopic chemical kinetics can carry out these electronic functions, then there are likely to be new approaches possible for the determination of complex reaction mechanisms, analogs of such determinations for electronic components. The discussion in the remainder of this chapter is devoted to illustrations of these topics; it can be skipped, except the last paragraph, without loss of continuity with chapter 5 and beyond. A neuron is either on or off depending on the signals it has received. A chemical neuron is a similar device.
Less
The topic of this chapter may seem like a digression from methods and approaches to reaction mechanisms, but it is not; it is an introduction to it. We worked on both topics for some time and there is a basic connection. Think of an electronic device and ask: how are the logic functions of this device determined? Electronic inputs (voltages and currents) are applied and outputs are measured. A truth table is constructed and from this table the logic functions of the device, and at times some of its components, may be inferred. The device is not subjected to the approach toward a chemical mechanism described in the previous chapter, of taking the device apart and testing its simplest components. (That may have to be done sometimes but is to be avoided if possible.) Can such an approach be applicable to chemical systems? We show this to be the case by discussing the implementation of logic and computational devices, both sequential machines such as a universal Turing machine (hand computers, laptops) and parallel machines, by means of macroscopic kinetics; by giving a brief comparison with neural networks; by showing the presence of such devices in chemical and biochemical reaction systems; and by presenting some confirming experiments. The next step is clear: if macroscopic chemical kinetics can carry out these electronic functions, then there are likely to be new approaches possible for the determination of complex reaction mechanisms, analogs of such determinations for electronic components. The discussion in the remainder of this chapter is devoted to illustrations of these topics; it can be skipped, except the last paragraph, without loss of continuity with chapter 5 and beyond. A neuron is either on or off depending on the signals it has received. A chemical neuron is a similar device.