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Computing Machinery Chapter 11: Alternative Architectures

Explore alternative architectures in computing, including Flynn's Taxonomy, parallel architectures, functional diagrams, and interconnections. Learn about 4-D Hypercube interconnections, pipeline processing, and various models such as PRAM, EREW, CREW, and CRCW. Discover the performance analysis of parallel architectures, including speed, speedup, efficiency, Amdahl's Law, and Gustafson's Law. Also, delve into the future of computer architecture and the challenges beyond Moore's Law.

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Computing Machinery Chapter 11: Alternative Architectures

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  1. Computing Machinery Chapter 11: Alternative Architectures

  2. Flynn's Taxonomy

  3. Parallel Architectures Functional Diagrams

  4. 4-D Hypercube Interconnections

  5. Pipeline Processing

  6. PRAM (Parallel Random Access Machine) EREW - Exclusive Read/Exclusive Write CREW - Concurrent Read/Exclusive Write ERCW - Not Used CRCW - Concurrent Read/Concurrent Write

  7. Concurrent Read/Exclusive Write (CREW) In this model, a particular address in shared memory can be read by multiple processors concurrently. However only one processor at a time can write to a particular address in shared memory. Concurrent means that the order in which two operations occur, does not affect the outcome (or state) of the system.

  8. Concurrent Read/Concurrent Write (CRCW) - In the concurrent read, concurrent write PRAM model, multiple processors can read from or write to the same address in shared memory concurrently. A number of alternative interpretations for the concurrent write operation have been studied. We can choose from a number of operations for concurrent write such as RANDOM, PRIORITY, MAX, and SUM.

  9. Parallel Architecture Performance Analysis Speed - The speed of a computing system is the amount of work accomplished (e.g. number of instructions completed) in a specified time. So we normally refer to processing speed in terms of instructions per second. Speedup - The speedup for a multi-processor system is the ratio of the time required to solve a problem using a multi-processor computer to the time required for a single-processor computer. Since speedup is the ratio of two quantities that have the same units (instructions per second), it is a unitless quantity.

  10. Efficiency - The efficiency of an n-processor multi-processor computer system is defined as the speedup of the multi-processor divided by the number of processors, n. Traditionally it has been assumed that efficiency cannot be greater than unity (1).

  11. Amdahl's Law

  12. Is Amdahl's Law a Speed Limit for Massively Parallel Processing?

  13. Gustafson's Law Scaled Speedup

  14. Deep Neural Networks possibly multiple hidden layers

  15. Selected Exercises

  16. The Future of Computer Architecture the end of Moore's Law It is believed that the ability to achieve process shrinks will continue as far as into the early 2010's but relatively soon. Specifically, the quantum mechanical properties of electrons and other atoms begin to dominate in the substrate when the feature size reaches around 50 nanometers. At sizes smaller than this, only a few electrons are needed to saturate the channel. Statistical fluctuations due to thermal effects will make the switching of transistors difficult to control.

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