NUMA Memory Locality Caching for Garbage Collection
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Solution Overview
Problem
In non-uniform memory access (NUMA) systems, garbage collection processes are time-consuming and lead to significant processing overhead, particularly due to the need to access memory locations that are faster for one set of processors than for another, causing long pauses in application programs and reducing system performance.
Innovation Solution
The method involves determining the locality domain of a memory unit and caching this information to facilitate affinity-based garbage collection, where garbage collection operations are allocated to the processor most closely coupled to the memory region, reducing unnecessary memory scans and improving processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If garbage collection processes access memory locations in NUMA systems, then memory management is performed, but processing overhead increases and system performance decreases
Solution Approach 1:
The patent applies preliminary action by pre-determining and caching the locality domain information of memory units before garbage collection operations are performed. The system calculates and stores the mapping between memory addresses and their corresponding locality domains in advance, so that during garbage collection, the processor can directly use this cached information to identify which processor should handle each memory location without performing time-consuming lookups at runtime. This resolves the contradiction by preparing the locality domain data beforehand, eliminating the processing overhead during actual garbage collection operations.
2Ease of operation
If processors access remote memory on different books, then memory access is enabled, but latency increases and bandwidth issues occur
Solution Approach 1:
The patent applies local quality by organizing garbage collection operations according to the locality domain of each memory unit. The system determines which processor has local affinity to each memory location and assigns the garbage collection task for that memory to the local processor. This ensures that processors primarily access local memory on their own book, minimizing remote memory accesses across the interconnect network. By making the garbage collection process locality-aware, the system maintains memory access capability while dramatically reducing access latency and network bandwidth consumption.
3Adaptability or versatility
If locality domain information is retrieved for each memory access, then affinity evaluation is enabled, but processing overhead increases
Solution Approach 1:
The patent applies copying by creating and maintaining a cached copy of the locality domain information for each memory unit. Instead of repeatedly querying the system to determine the locality domain of memory locations during garbage collection, the system pre-computes and stores this information in a cache structure. When a garbage collection operation needs to process a memory location, it simply retrieves the pre-stored locality domain information from the cache, avoiding repeated complex evaluations. This copying approach preserves the adaptability of affinity evaluation while significantly reducing the processing overhead associated with repeated queries.
Data Source
AI summary
Processing within a computing environment is facilitated by ascertaining locality domain information of a unit of memory to processing capability within the computing environment. Once ascertained, the locality domain information of the unit of memory may be cached in a data structure to facilitate one or more subsequent lookups of the locality domain information associated with one or more affinity evaluations of the unit of memory to processing capability of the computing environment.