Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • plattsa
    Member
    • Mar 2009
    • 17

    NUMA v SMP for Sequence Assembly

    Hi, we're increasing the size of the genomes we're assembling using GAII reads. Our old assembly server had an SMP architecture and worked fairly well but was limited in its RAM (96GB). With assemblers such as Velvet we're looking to move up to a 256GB RAM solution and had considered the Dell R910 (1TB Max RAM), Sunfire x4640 and HP DL785.

    However to varying degrees these are all NUMA solutions with banks of RAM associated with a specific CPU/CPUs. I am a little concerned about the possibility of high latency where a single threaded process needs to access close to the entire contents of RAM. Essentially it seems a lot of the data would have to pass through several memory bridges before arriving at the active core with the consequent risk of a stalled CPU pipeline.

    Cold anyone comment on whether this should be a concern or whether technologies such as quickpath can essentially get around this?

    Thanks for your thoughts.
  • Zigster
    Jeremy Leipzig
    • May 2009
    • 117

    #2
    Hmmm...even the largest (100M read) Velvet assemblies on our 256GB Dell Poweredge machine only take about three hours.

    Does anyone make non-NUMA boxes?
    --
    Jeremy Leipzig
    Bioinformatics Programmer
    --
    My blog
    Twitter

    Comment

    • plattsa
      Member
      • Mar 2009
      • 17

      #3
      Thanks - that's reassuring to hear!

      In the x86 world I think you're right, there's not a lot of SMP kit in the 256GB+ range. But in the power (IBM P series) and perhaps in the other high end risc processors I think it's still possible.

      Comment

      • plattsa
        Member
        • Mar 2009
        • 17

        #4
        I had the below from Dell on this topic:

        There are two situations where remote memory accesses are unavoidable. First, processes that require more memory than what is available to a single processor. Second, processes that spawn more threads than available cores within the local socket. CPU and memory affinity are not appropriate in either case. 11G servers have a BIOS feature called Node Interleaving that stripes data across both memory controllers when enabled. Interleaved accesses are slower than local-only accesses because every other operation traverses the QPI link. However, this feature prevents the worst case scenario where a process is forced to access remote memory at every operation.

        Comment

        Latest Articles

        Collapse

        • SEQadmin2
          Advanced Sequencing Platforms Tackle Neuroscience’s Toughest Genomics Problems
          by SEQadmin2



          Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
          ...
          07-09-2026, 11:10 AM
        • SEQadmin2
          Cancer Drug Resistance: The Lingering Barrier to Rising Survival
          by SEQadmin2



          Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.

          There is no single reason why many patients don’t respond to treatment as expected. Cancer is...
          07-08-2026, 05:17 AM
        • GATTACAT
          Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
          by GATTACAT
          Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
          07-01-2026, 11:43 AM

        ad_right_rmr

        Collapse

        News

        Collapse

        Topics Statistics Last Post
        Started by SEQadmin2, 07-13-2026, 10:26 AM
        0 responses
        25 views
        0 reactions
        Last Post SEQadmin2  
        Started by SEQadmin2, 07-09-2026, 10:04 AM
        0 responses
        35 views
        0 reactions
        Last Post SEQadmin2  
        Started by SEQadmin2, 07-08-2026, 10:08 AM
        0 responses
        22 views
        0 reactions
        Last Post SEQadmin2  
        Started by SEQadmin2, 07-07-2026, 11:05 AM
        0 responses
        34 views
        0 reactions
        Last Post SEQadmin2  
        Working...