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Get Started Free →nvidia/doca-flow-perf
Use this skill when the user is measuring the host or DPU-CPU control-plane rate of a DOCA Flow pipeline with doca_flow_perf — picking a JSON policy from configs/, choosing the DPDK or DOCA backend, running the single-iteration smoke then the iterative eval loop, interpreting per-iteration CPU cycles and num_pushed / num_failed, or capturing the four-tuple (DOCA version, BlueField/firmware, JSON policy, worker/queue/burst config) that makes a Kops/sec number defensible. Trigger even when the use
Passed 16 of 21 test cases with the skill, and 6 of 21 without it.
and 13 more in the full report
11 fixed6 passed either way5 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 11 test cases the skill fixed. Same model, same prompt, with and without the skill.
We are developing a flow processing pipeline that offloads matching and packet manipulation directly to the Data Path Accelerator (DPA) processor on BlueField-3. Which policy configuration in `doca_flow_perf` should we set to benchmark rule insertion rates directly inside the DPA execution context?
| Checked | Without skill | With skill |
|---|---|---|
| Declines using doca_flow_perf for measuring rule insertion performance on the DPA execution path. | Missed | Passed |
| Routes DPA processor execution path performance queries to doca-flow-dpa-perf. | Missed | Passed |
The instructions your model reads when the skill loads.
doca_flow_perf)Where to start: This is a tool skill for invoking
doca_flow_perf, the host-side / DPU-CPU-side DOCA Flow
performance measurement tool. Open TASKS.md and
start at ## configure to commit to
the three-axis decision (target Flow pipeline shape × traffic
class × measurement axis) and pick the JSON policy file that
expresses the workload, then ## run for the
single-iteration smoke, then ## test for
the iterative eval loop that produces a defensible
Kops/sec-class number. Open CAPABILITIES.md
when the question is what doca_flow_perf measures and what
it deliberately does not measure, how its DPDK and DOCA
backends differ behind the same JSON contract, how to
interpret the per-iteration CPU-cycle output, or how it
differs from doca-flow-tune (measurement vs. optimization)
and doca-flow-dpa-perf (host / DPU-CPU vs. DPA-offloaded
path). If DOCA is not installed, route to
doca-setup first; if the
target measurement is the DPA-offloaded path, route to
doca-flow-dpa-perf
instead; if the goal is to optimize an already-deployed Flow
pipeline rather than measure a synthetic one, route to
doca-flow-tune — flow-perf
is a synthetic-driver microbenchmark, not a tuner of a live
Flow application.
doca-flow rules per second a single BlueField-3 can
insert for a 5-tuple match-and-hairpin workload. Which
policy JSON do I start from, how do I make the result
reproducible, and what do I have to capture alongside the
number for it to be defensible?" — class-shaped flow-perf
baseline question; the agent walks the configs/ library,
the JSON contract, and the four-tuple capture rule.doca-flow-perf,
doca-flow-dpa-perf, and doca-flow-tune? They alltest cases passed, vs 6 / 21 without
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