1 / 10

NUMA aware heap memory manager

NUMA aware heap memory manager . How to use our resources wisely in multi-thread and multi - proccessor systems Michael Shteinbok Shai Ben Nun Supervisor: Dmitri Perelman. What’s the problem?.

ray
Download Presentation

NUMA aware heap memory manager

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. NUMA aware heap memory manager How to use our resourceswisely in multi-threadand multi-proccessorsystems Michael Shteinbok Shai Ben Nun Supervisor: Dmitri Perelman

  2. What’s the problem? • While increasing number of cores/processors seems to increase the performance in proportion, it usually increases in lower numbers and sometimes even slows us down.

  3. Ok, But Why? • Some physical issues can still cause a bottleneck. For example Memory Access and Management. • UMA – Uniformed Memory Access

  4. Solution - NUMA • Non Uniform Memory Access - each CPU has it’s own close memory with quick access. • One processor can access the other memory units but with slower BW. • The NUMA API lets theprogrammertomanagethememory.

  5. HowOneManagesTheMemory? • When we allocate and free, we are blind to the process in the background. Forthisneedwehavedifferentlibfunction. (glibc, TCMalloc, TCMalloc NUMA Aware) • The article refers to this management problem and offers the TCMalloc NUMA Aware heap manager http://developer.amd.com/Assets/NUMA_aware_heap_memory_manager_article_final.pdf

  6. Performance Change • The Previous solutions(more BW, more local access):

  7. Project Goals • Improving the current TCMallocnuma aware in scenarios it losses performance • Managing wisely the memory of different cores and offer a new “read” function that will be faster (TBD)

  8. Problem In Current Solution • When thread frees memory that was allocated by another thread (on another numa node) we can get performance loss Thread A Thread A Thread B X = Allocate X = malloc Thread A Free pool Free (X) Free (X)

  9. Our Benchmark • Each couple of threads on a different numa node. • 8 quad-cores processors => Total 16 couples. Allocator Thread Alloc Queue Free Thread Alloc Rand List (5000) First-touch policy Access Memory

  10. Achieving Project Goals Step By Step • Learn how does the TCMalloc work • Find scenarios that makes current TCM to loss performance. • Sort the scenarios by most likely to occur in real environment • Implement a support in these scenarios • Make new TCMalloc to get better performance!

More Related