Multiprocessor Computational Density Optimization
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Solution Overview
Problem
Multiprocessor systems face challenges in optimizing computational density due to increasing communications latency and heat dissipation issues, as processor power and bandwidth improvements are limited by the speed of light, making it difficult to balance processing power, communications bandwidth, and latency while ensuring adequate heat dissipation.
Innovation Solution
A system and method that maximizes computational power within specified physical volume and heat dissipation constraints by balancing the use of higher-powered processors placed further apart with lower-powered processors placed closer together, using Multi-Disciplinary Design Optimization (MDO) to select the optimal processor design that balances power consumption, performance, and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If processors are placed closer together to reduce communications latency and increase computational density, then communications latency is reduced and computational density increases, but heat dissipation becomes more difficult
Solution Approach 1:
The system changes the parameter of processor power consumption to optimize the balance between computational density and heat dissipation. By selecting processors with appropriate power consumption levels and adjusting their placement distances, the system achieves optimal computational density while maintaining acceptable heat dissipation characteristics.
2Power
If higher-powered processors are used to increase computational power, then processing power increases, but heat generation increases making heat dissipation more difficult
Solution Approach 1:
The system optimizes the parameter of processor power consumption by evaluating multiple processor options with different power characteristics. The MDO process selects processor power levels that maximize computational power while maintaining heat dissipation within acceptable limits, achieving an optimal balance between processing power and thermal management.
3Temperature
If processors are placed further apart to improve heat dissipation, then heat dissipation improves, but communications latency increases and computational density decreases
Solution Approach 1:
The system adjusts the parameter of processor placement distance to find the optimal balance between heat dissipation and communications latency. By varying the distance between processors and evaluating the trade-offs, the system determines the optimal spacing that provides adequate heat dissipation while minimizing communications latency and maintaining high computational density.
Data Source
AI summary
A system and method of designing a computer system having a plurality of processors. A computational density is selected for the computer system, wherein the computational density is expressed as a function of a desired computational power for a given volume. A number of processors is selected for used in the computer system and the desired computational power is allocated across the selected number of processors. One or more constraints are selected and a particular processor is designed or selected to meet the allocated processor computational power and the constraint.