Connected Managed Runtime Code Optimization
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Solution Overview
Problem
Standalone managed runtime environments are isolated and self-contained, limiting their performance and resource utilization to local resources, leading to inefficiencies as they repeat tasks independently without sharing runtime information or optimizing code across devices with similar behavior profiles.
Innovation Solution
A connected managed runtime environment that communicates with external entities via networks to share optimized code units and speculative assumptions, leveraging external computational power, storage, and analytical capabilities to enhance performance and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a managed runtime environment is isolated and self-contained, then it maintains simplicity and reliability, but its performance and resource utilization are limited to local resources
Solution Approach 1:
The system segments the code optimization functionality into separate external entities that can be independently managed and executed. These external entities perform speculative optimizations locally and share results through a network, dividing the overall optimization task across multiple independent components rather than requiring one centralized complex system.
Solution Approach 2:
The patent introduces an intermediary mechanism (the network communication infrastructure and protocol) that enables information exchange between isolated managed runtime environment instances. This intermediary allows them to share speculative assumptions and optimized code units without requiring direct integration or loss of isolation, thus maintaining simplicity while enabling collaborative optimization.
2Productivity
If a standalone managed runtime environment utilizes only local resources, then it maintains reliability and isolation, but it repeats tasks independently without sharing runtime information
Solution Approach 1:
The system performs preliminary speculative optimizations in advance based on observed runtime patterns and assumptions. By pre-computing optimized code units with associated speculative assumptions before they are needed, the system eliminates the need for repeated independent optimization tasks across different instances, improving efficiency while maintaining information isolation.
Solution Approach 2:
The patent implements a copying mechanism where optimized code units and their associated speculative assumptions are replicated and shared across multiple managed runtime environment instances via the network. This allows instances to benefit from previously computed optimizations without exchanging their actual runtime information, thus improving efficiency while preserving information isolation through cryptographic or protocol-based copying.
3Loss of time
If managed runtime environments share optimized code and speculative assumptions across networks, then resource consumption is reduced and startup times improve, but security risks and anomaly detection complexity increase
Solution Approach 1:
The system applies preliminary anti-action by pre-validating and verifying optimized code units and speculative assumptions before they are shared across the network. Security checks, anomaly detection, and consistency validations are performed in advance during the optimization and sharing process, preventing potentially harmful or incorrect code from being executed, thus reducing security risks while enabling fast startup through code sharing.
Data Source
AI summary
A first instance of a managed runtime environment is provided. An optimized version of a code unit and a corresponding set of one or more speculative assumptions are received at the first instance of the managed runtime environment, wherein the optimized version of the code unit produces the same logical results as the code unit unless at least one of the set of one or more speculative assumptions is not true, and wherein the optimized version of the code unit and the corresponding set of one or more speculative assumptions are generated by an entity that is different from the first instance of the managed runtime environment. The optimized version of the code unit is executed at the first instance of the managed runtime environment. Whether the set of one or more speculative assumptions hold true is monitored at the first instance of the managed runtime environment.