~/talk

Turbocharge ANNS on Real Processing-in-Memory by Enabling Fine-Grained Per-PIM...

Talkat USENIX ATC '25 · 2025-07-07..07-09· [machine-learning]
name:Puqing Wu
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name:Jing Wang
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name:Kai Ren
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PIMANN retrofits UPMEM by tapping an undocumented per-PU control interface to switch DDR ownership and run a persistent PIM kernel that eliminates inter-batch idle time, plus per-PU query dispatching with cluster slicing and hotness-based replication to fix intra-batch imbalance. Implementation modifies the UPMEM driver and runs on SIFT1B and SPACE1B, raising PIM utilization from 18.2% to ~80% and boosting throughput by 2.4–10.4× while cutting average latency 32–43% and improving throughput-per-watt up to 2.5×.

AI-written summary · about

  1. 0:00Kim Alen and PIM-based ANNS
  2. 1:19ANNS fundamentals and IBFPQ
  3. 3:11CPU/GPU ANNS limitations
  4. 4:15UPNM PIM hardware
  5. 5:07PIM batch scheduling bottlenecks
  6. 7:40Fine-grained per-PU scheduling
  7. 9:05System architecture and PIM kernel
  8. 10:10Persistent PIM kernel details
  9. 12:23Driver changes for per-PU control
  10. 13:29Per-PU query dispatching
  11. 15:18Evaluation setup and datasets
  12. 16:23PIM throughput improvements
  13. 17:33Latency and power efficiency
  14. 18:17Conclusion and open-source
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