Memory-System Message Passing for CPU-Free Peripheral Data Access
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Solution Overview
Problem
Conventional systems inefficiently manage data access communications between peripheral devices like GPUs and SSDs due to CPU involvement, degrading system performance, and struggle to improve cache hit ratios through ineffective cache policies.
Innovation Solution
Implementing a message passing interface (MPI) in memory sub-systems allows direct communication between peripheral devices without CPU assistance, enabling predictive data movements across different tiers of memory using machine learning techniques to optimize data placement and reduce unnecessary data transfers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If CPU involvement is used to manage data access communications between peripheral devices, then data access can be coordinated and controlled, but system performance degrades due to CPU bottlenecks
Solution Approach 1:
The patent extracts the data access coordination function from the CPU by implementing a message passing interface directly in the memory sub-system. This allows peripheral devices to communicate and coordinate data access operations independently without burdening the CPU, thereby resolving the contradiction between maintaining reliable coordination and avoiding performance degradation.
Solution Approach 2:
The patent introduces an intermediary message passing interface layer within the memory sub-system that mediates between peripheral devices and the memory components. This intermediary handles data access coordination locally, preventing CPU bottlenecks while maintaining reliable coordination through structured message passing protocols.
2Ease of manufacture
If conventional cache policies are used, then cache operations are simple to implement, but cache hit ratios remain low due to ineffective data placement
Solution Approach 1:
The patent applies preliminary action by using machine learning models to predict which data will be accessed next and pre-positioning that data in the cache before it is actually needed. This predictive caching strategy significantly improves cache hit ratios compared to conventional reactive policies, while the ML model can be integrated into existing cache controllers.
Solution Approach 2:
The patent changes the fundamental parameter of cache decision-making from rule-based heuristics to machine learning-based predictions. By transitioning from static cache policies to dynamic ML-driven policies, the system achieves higher cache hit ratios while maintaining implementation feasibility through incremental integration of ML models.
Data Source
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AI summary
A memory system having a plurality of memory components and a controller, operatively coupled to the plurality of memory components to: store data in the memory components; communicate with a host system via a bus; service the data to the host system via communications over the bus; communicate with a processing device that is separate from the host system using a message passing interface over the bus; and provide data access to the processing device through communications made using the message passing interface over the bus.