Hybrid Communication Engine for Dynamic Interconnect Selection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
High-performance computing solutions face challenges with increasing latency and energy consumption in data transmissions, especially with longer distances and larger chip sizes, due to the heterogeneity of industry solutions for interconnects.
Innovation Solution
A hybrid communication engine dynamically selects between wired and wireless interconnects based on static and dynamic parameters such as latency, message size, physical distance, energy cost, and current congestion, using a combination of hardware and software to determine the best interconnect for data routing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single interconnect technology is used for data transmission, then device complexity is reduced, but latency and energy consumption increase with longer distances and larger chip sizes
Solution Approach 1:
The system segments the interconnect architecture into multiple specialized interconnects (e.g., wired interconnect for short-distance communication, wireless interconnect for longer-distance communication). Each interconnect is optimized for specific communication scenarios, allowing the system to reduce latency by selecting the appropriate interconnect based on distance and communication requirements rather than using a single generic interconnect for all scenarios.
Solution Approach 2:
The system dynamically selects between different interconnect technologies based on real-time conditions such as communication distance, data size, and current interconnect status. This dynamic adaptation allows the system to optimize for low latency in each specific scenario, transitioning between wired and wireless interconnects as needed rather than being constrained by a fixed interconnect architecture.
2Device complexity
If a single interconnect technology is used for data transmission, then device complexity is reduced, but energy consumption increases with longer distances and larger chip sizes
Solution Approach 1:
The system divides the interconnect architecture into multiple energy-efficient segments, each optimized for specific communication scenarios. Wired interconnects are used for energy-efficient short-distance communication, while wireless interconnects handle longer-distance communication. This segmentation prevents the energy waste that would occur if a single high-performance interconnect were used for all communication distances.
Solution Approach 2:
The system changes operational parameters by selecting different interconnect technologies based on communication requirements. By adjusting the selection of interconnect type (wired vs. wireless) according to distance, data size, and current system state, the system optimizes energy consumption for each transmission scenario rather than operating at high energy consumption levels for all scenarios.
3Loss of time
If dynamic selection between multiple interconnects is implemented, then latency and energy consumption are reduced, but device complexity increases
Solution Approach 1:
The system performs preliminary calibration of multiple interconnects to establish baseline performance characteristics and selection criteria. By pre-configuring selection tables and calibration data that map communication scenarios to optimal interconnect choices, the system reduces the complexity of real-time decision-making. The preliminary action of calibration creates lookup tables and selection rules that simplify runtime interconnect selection while maintaining low latency performance.
4Use of energy by moving object
If dynamic selection between multiple interconnects is implemented, then energy consumption is reduced, but device complexity increases
Solution Approach 1:
The system performs preliminary calibration of multiple interconnects to establish baseline performance characteristics and selection criteria. By pre-configuring selection tables and calibration data that map communication scenarios to optimal interconnect choices, the system reduces the complexity of real-time decision-making. The preliminary action of calibration creates lookup tables and selection rules that simplify runtime interconnect selection while maintaining energy efficiency.
Solution Approach 2:
The system implements feedback mechanisms that monitor interconnect performance and usage patterns, using this information to refine interconnect selection decisions. Calibration data and performance metrics feed back into the selection logic, allowing the system to adapt to changing conditions while maintaining energy efficiency. This feedback loop optimizes energy consumption without requiring complex real-time analysis, as the system learns from past performance data.
Data Source
AI summary
Systems, apparatuses, and methods for dynamically selecting between wired and wireless interconnects for sending packets are disclosed. A system includes at least a hybrid communication engine and a plurality of interconnects for connecting to various end-points. The communication engine dynamically discovers and utilizes the best interconnect technology available in between given end-points. The communication engine dynamically chooses the physical interconnect that is best suited at any given time to send data from one source to one or multiple destinations. This communication can be either on-chip or across nodes. The communication engine makes a decision based on a set of predetermined parameters that can be re-adjusted by the application layer, such as latency of the transmission, message data size, physical distance from source to destination, the energy cost, and the current congestion on the alternative interconnects.