Dynamic Thread Mapping for CPU Core Latency
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Solution Overview
Problem
Modern CPU performance is hindered by resource starvation due to latency differences between local and non-local memory accesses, leading to inefficient use of load/store buffers and software overhead in managing thread assignments for simultaneous multi-threading (SMT) capabilities.
Innovation Solution
Implementing hardware registers to track and classify threads based on memory access latency, allowing for dynamic thread mapping and migration to cores with similar memory access types, and applying dynamic voltage and frequency scaling (DVFS) to optimize CPU performance by maximizing cores with uniform memory access types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If simultaneous multi-threading (SMT) is implemented to increase CPU performance, then processing capacity is improved, but software overhead increases
Solution Approach 1:
The patent implements self-service by enabling CPU hardware to automatically track, classify, and manage thread memory access patterns without external software intervention. Hardware registers autonomously monitor memory accesses and classify threads as local-memory-bound or non-local-memory-bound, eliminating the need for operating system software to perform these management functions.
Solution Approach 2:
The patent replaces the software-based thread management system with a hardware-based system. Instead of using software to track and classify thread memory access patterns, the invention uses hardware registers and circuitry to automatically perform classification, thereby reducing software overhead and improving processing efficiency.
2Adaptability or versatility
If threads are assigned to CPU cores without classification, then scheduling flexibility is maintained, but resource starvation occurs due to latency differences
Solution Approach 1:
The patent applies local quality by differentiating thread management based on their specific memory access characteristics. Threads are classified into different categories (local-memory-bound and non-local-memory-bound) and assigned to appropriate CPU cores, allowing each core to be optimized for its assigned thread type rather than treating all threads uniformly.
Solution Approach 2:
The patent segments the CPU core pool based on memory access patterns. By dividing threads into distinct categories and assigning them to different cores, the system creates specialized processing units that handle specific memory access types, preventing resource starvation while maintaining overall scheduling flexibility.
3Quantity of substance
If load/store buffers are shared across all threads, then buffer utilization is maximized, but performance decreases due to latency variations
Solution Approach 1:
The patent applies local quality by allocating buffer resources according to the specific needs of different thread types. Instead of uniformly sharing buffers across all threads, the system provides differentiated buffer access based on memory access patterns, ensuring that threads with different latency requirements receive appropriate buffer resources.
Data Source
AI summary
In one example, a central processing unit (CPU) with dynamic thread mapping includes a set of multiple cores each with a set of multiple threads. A set of registers for each of the multiple threads monitors for in-flight memory requests the number of loads from and stores to at least a first memory interface and a second memory interface by each respective thread. The second memory interface has a greater latency than the first memory interface. The CPU further has logic to map and migrate each thread to respective CPU cores where the number of cores accessing only one of the at least first and second memory interfaces is maximized.