Cache Slice Allocation for CPU Thread Performance
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Solution Overview
Problem
Current computing systems face performance issues when handling a large number of objects with limited worker threads, leading to CPU cache thrashing and inefficient resource utilization, especially when both procedural and message-passing approaches are used concurrently.
Innovation Solution
A cache slice allocation algorithm that dynamically assigns exclusive or shared cache slices to database objects based on their priority, allowing for efficient load balancing and resource distribution across multiple objects and threads, utilizing simultaneous multi-threading capabilities to optimize CPU resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a worker thread frequently switches between multiple objects to process, then the worker thread can handle more objects, but the CPU cache is thrashed causing performance to degrade
Solution Approach 1:
The CPU cache is segmented into multiple cache slices, with each slice dedicated to caching data for a specific object. When a worker thread processes an object, that object's data is cached in its dedicated slice, preventing cache thrashing even when the thread switches between multiple objects. This segmentation allows the worker thread to maintain high adaptability while preserving processing performance.
2Reliability
If locks are used for synchronization in procedural programming, then exclusive access to shared data is ensured, but thread concurrency is limited and performance scales poorly
Solution Approach 1:
A message queue serves as an intermediary between multiple worker threads and the processing system. Instead of worker threads directly competing for shared data with locks, they post messages to the queue. The system processes messages sequentially, ensuring data correctness without requiring thread synchronization locks. This intermediary mechanism enables high thread concurrency while maintaining reliability.
3Quantity of substance
If the number of worker threads is limited while the number of objects is large, then resource utilization is controlled, but cache thrashing occurs and performance collapses
Solution Approach 1:
The cache is segmented into multiple slices, with each slice dedicated to a specific object. This allows a limited number of worker threads to handle a large number of objects without cache thrashing, as each object's data resides in its dedicated cache slice. The segmentation enables controlled resource utilization while maintaining high processing performance.
Solution Approach 2:
Each cache slice is assigned a specific quality characteristic - dedication to a particular object. This local quality ensures that when a worker thread processes any object, that object's data is always available in its dedicated slice, eliminating cache conflicts and maintaining high performance even with limited threads handling many objects.
Data Source
AI summary
A central processing unit (CPU) forming part of a computing device, initiates execution of code associated with each of a plurality of objects used by a worker thread. The CPU has an associated cache that is split into a plurality of slices. It is determined, by a cache slice allocation algorithm for each object, whether any of the slices will be exclusive to or shared by the object. Thereafter, for each object, any slices determined to be exclusive to the object are activated such that the object exclusively uses such slices and any slices determined to be shared by the object are activated such that the object shares or is configured to share such slices.