This talk looks at common and maybe not so common pitfalls in writing high-performance distributed systems in Rust. We will look at topics ranging from memory layout having an outsize impact on the overall latency in a distributed system, to reducing the memory footprint of scatter-gather operations, to writing custom SMID kernels to speed up compute-intensive parts of both read and write paths. Performance can be gained in surprising places, where often small changes have a big impact.

1. Brought to you by
Pitfalls in Writing High-
Performance Systems in Rust
Marek Galovic
Staff Software Engineer at Pinecone

2. Reduce Memory Footprint of
Scatter-Gather Operations

3. shard #1
shard #3
shard #4
shard #5
shard #2
shard #n
client

4. join_all

5. select_all

6. Optimized Memory Layout

7. Indirect Access

8. 0 1 2 3 … n
0x55f283eaaad0 0x55f283eabce0 0x55f283eadd80 0x55f283eb0e20

9. Cache Optimal Access

10. 0 1 2 3 … n
0x562fc238cad0 0x562fc238cc50 0x562fc238cdd0 0x562fc238cf50 0x562fc238cf50

12. Custom SIMD Kernels

13. Native Implementation

15. AVX2 Implementation

16. AVX2 Implementation

17. AVX2 Implementation

19. AVX2 Instruction Level Parallelism

20. AVX2 Instruction Level Parallelism

21. AVX2 Instruction Level Parallelism

22. AVX2 Instruction Level Parallelism

23. AVX2 Instruction Level Parallelism

24. AVX2 Instruction Level Parallelism

26. Data Layout

27. Data Layout v.1

28. Data Layout v.2

29. Data Layout v.3

30. Data Layout v.3

31. Data Layout v.4

32. Container
Dataset #1 Dataset #2
Runtime Max RSS Runtime Max RSS
RadixTreeSet 5.74s 558.65 MB 3.31s 283.25 MB
HashSet 6.37s 2062.06 MB 3.62s 1205.06 MB
BTreeSet 6.05s 1276.07 MB 2.76s 867.42 MB

33. Brought to you by
Marek Galovic
marek@pinecone.io
We are hiring! - www.pinecone.io/careers