Memory-Aware Thread Placement for Lower NUMA Access Latency
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Solution Overview
Problem
Existing systems face challenges in optimizing thread distribution across multiple processing circuitries due to varying memory access times, leading to increased latency and reduced throughput, especially in Non-Uniform Memory Access (NUMA) systems, where memory access times depend on physical location and access metrics.
Innovation Solution
Collecting and analyzing thread statistical values to identify a preferred memory area for each thread, and configuring processing circuitries associated with that area to execute the thread, thereby optimizing memory access patterns and improving system performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If threads are distributed across multiple processing circuitries in a NUMA system, then system throughput is increased, but memory access latency increases due to non-uniform access times to different memory areas
Solution Approach 1:
The system performs preliminary analysis of thread memory access patterns before final thread placement. By collecting statistical data about which memory areas threads access most frequently and pre-configuring threads to be executed by processing circuitries associated with those memory areas, the system proactively optimizes memory access latency before threads actually execute, thereby resolving the contradiction between throughput and latency
Solution Approach 2:
The patent applies local quality by assigning different threads to different processing circuitries based on their specific memory access characteristics. Each thread is analyzed individually to determine its preferred memory area, and then placed on the processing circuitry locally associated with that memory area. This localized optimization ensures that each thread experiences minimal memory access latency while the system maintains high overall throughput
2Speed
If statistical analysis of memory access patterns is performed to optimize thread placement, then memory access performance is improved, but system complexity increases due to additional monitoring and configuration mechanisms
Solution Approach 1:
The system implements self-service by automatically collecting memory access statistics, analyzing patterns, and configuring thread-to-processing-circuitry mappings without requiring manual intervention. The processing circuitries themselves generate and provide the statistical data about their memory access patterns, and the system autonomously uses this data to optimize thread placement, thereby reducing operational complexity while maintaining high memory access speeds
Solution Approach 2:
The patent employs feedback mechanisms where the system continuously monitors memory access patterns of executing threads and uses this feedback information to dynamically adjust thread placement decisions. The statistical data collected from actual memory access behavior provides real-time feedback that guides the optimization process, enabling the system to adapt to changing workloads and maintain optimal performance without complex manual configuration
Data Source
AI summary
A system for executing a plurality of software threads, comprising: a plurality of processing circuitries; a plurality of memory areas connected to the processing circuitries, each memory area associated with at least one of the processing circuitries; and at least one hardware processor, connected to the processing circuitries and configured for: in each of a plurality of iterations: while the processing circuitries execute the software threads, collecting for each thread a plurality of thread statistical values indicative of a plurality of memory accesses to at least some of the memory areas performed when executing the thread; for at least one thread, performing an analysis comprising the thread statistical values thereof to identify a preferred memory area of the plurality of memory areas; and configuring one of the at least one processing circuitry associated with the preferred memory area to execute the at least one thread.