dau began on dpv1 with a 5 GB NYSE TAQ dataset and a concrete task: calculate OHLCV bars. Staged resident, repeated queries ran in 0.92 seconds against 1.5 seconds on the CPU—39% - lower per-query latency, every result matched to the software golden. dpv2 now carries that - work further: a fused temporal-finance workflow—as-of join, derived features, time bars and - rolling moments in a single pass, with no intermediate ever written back to memory—runs in - 11.5 ms against 31.4 ms for the same workload on an 18-core laptop, bit-exact. The - accelerator costs a fraction of the machine it outruns. + lower per-query latency, every result matched to the software golden. dpv2 is commodity + hardware doing real work: a consumer-grade FPGA card that costs about $700, in a + consumer-grade desktop with a quad-core Intel Core i7. With a six-million-row table resident + on the card, Polars and the card working the same scan together finished in 4.2 ms against + 10.4 ms for the CPU alone, using all of its threads. That is 2.5x faster, and every result + matched the software golden at every one of the 164 split points we measured. The scheduler + chose the split from measured costs; nobody tuned it by hand.
204K LUTs · 10 GB DDR3 · PCIe x8
Two memory systems (2 GB onboard for bandwidth, 8 GB SODIMM for resident capacity) and - eight parallel lanes. Where the fused temporal workflow now beats the CPU baseline. + eight parallel lanes. CPU and card together: 2.5x the CPU alone on a resident scan, + bit-exact.