TLB update-hint algorithm as a scalable TLB consistency management solution for CC-NUMA multiprocessors. By using a lazy TLB invalidation approach, we reduced the number of unnecessary processor interruptions and idle-waiting time, and achieved a high level of scalability. Using a shared memory simulator, we evaluated the TLB update-hint algorithm. For performance comparison, we also simulated the TLB shootdown algorithm, one of the most popular TLB consistency algorithms. The simulations demonstrated that the TLB update-hint algorithm scales well in systems with a large number of processors. At 64 node systems, the TLB update-hint algorithm shows 4787% better performance than the TLB shootdown algorithm." />
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TLB Update-Hint: A Scalable TLB Consistency Algorithm for Cache-Coherent Non-uniform Memory Access Multiprocessors

Byeonghag SEONG
Donggook KIM
Yangwoo ROH
Kyuho PARK
Daeyeon PARK

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E87-D    No.7    pp.1682-1692
Publication Date: 2004/07/01
Online ISSN: 
DOI: 
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Section on Hardware/Software Support for High Performance Scientific and Engineering Computing)
Category: Networking and System Architectures
Keyword: 
TLB consistency,  TLB shootdown,  cache-coherent non-unifrom memory access,  shared memory multiprocessor,  operating system,  

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Summary: 
Shared memory multiprocessors in which each processor has its own TLB must manage consistency among TLBs and a page table. As the large-scale CC-NUMA (cache-coherent non-uniform memory access) shared memory multiprocessors become popular, it is important for TLB consistency management algorithms to be highly scalable. In this paper, we propose a TLB update-hint algorithm as a scalable TLB consistency management solution for CC-NUMA multiprocessors. By using a lazy TLB invalidation approach, we reduced the number of unnecessary processor interruptions and idle-waiting time, and achieved a high level of scalability. Using a shared memory simulator, we evaluated the TLB update-hint algorithm. For performance comparison, we also simulated the TLB shootdown algorithm, one of the most popular TLB consistency algorithms. The simulations demonstrated that the TLB update-hint algorithm scales well in systems with a large number of processors. At 64 node systems, the TLB update-hint algorithm shows 4787% better performance than the TLB shootdown algorithm.

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