Multi-Die Telemetry Control for Scalable Performance Monitoring
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Solution Overview
Problem
Existing performance monitoring systems for multi-die computing systems face challenges in efficiently and effectively providing static and dynamic performance monitoring across multiple dies without requiring monitoring consumers to be aware of underlying hardware complexity, while maintaining quality of service and security, and supporting multiple telemetry streams concurrently.
Innovation Solution
A distributed performance telemetry system that abstracts the multi-die nature of chips by facilitating centralized control and data collection across dies, supporting multiple telemetry consumers, and enabling flexible, secure, and scalable performance monitoring with minimal hardware and memory overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If performance monitoring is implemented across multiple dies, then measurement precision and reliability are improved, but device complexity increases due to distributed hardware components
Solution Approach 1:
Multiple data generators from different dies are merged into a unified telemetry subsystem controlled by a single control path. The control path on one die coordinates and aggregates performance data from multiple dies, creating a consolidated monitoring system that maintains precision while reducing overall complexity.
Solution Approach 2:
The telemetry subsystem is designed with universal control capabilities that can monitor performance across multiple dies through a single control interface. The control path can selectively enable and configure data generators on different dies, providing multi-functional performance monitoring without requiring separate control paths for each die.
2Adaptability or versatility
If multiple telemetry streams are supported concurrently, then adaptability and versatility are improved, but device complexity increases due to additional control and data collection mechanisms
Solution Approach 1:
The control path is designed to dynamically enable and disable data generators based on monitoring needs. The system can adaptively activate specific data generators on specific dies only when required for particular telemetry streams, providing versatility while maintaining simplicity by avoiding permanent activation of all possible monitoring components.
Solution Approach 2:
Different data generators are configured with local quality characteristics tailored to their specific functions and locations. Each data generator can be independently enabled or disabled based on local monitoring requirements, allowing the system to provide differentiated monitoring capabilities without uniformly increasing complexity across the entire system.
3Ease of operation
If centralized control is implemented across distributed dies, then ease of operation is improved, but loss of time increases due to cross-die communication overhead
Solution Approach 1:
The control path acts as an intermediary that localizes control operations. Instead of requiring direct communication between all control elements and all data generators across dies, the control path on one die mediates control signals, enabling centralized control while minimizing cross-die communication overhead by consolidating control functions in a single location.
Data Source
AI summary
Computing system performance monitors provide on-chip control, selection, collection, coalescing and communication of behavior and other processing-indicating data of high performance single- and multi-die computing and processing systems, such as for use in multi-chip-module and/or multi-instanced graphics processing units (GPUs) and/or systems-on-chips (SOCs). Commands and data records can be forwarded between modules to abstract the processing system from profilers and other data report consumers. Quality of Service and security isolation for different command and data report streams is maintained.