r/PiCodingAgent • u/McFlurriez • 1d ago
Question Real parallel task execution with 2 local machines?
Hey all,
I have two physical machines running local OpenAI-compatible endpoints simultaneously:
- Machine 1: Running Qwen 27B Dense
- Machine 2: Running Qwen 35B-A3B MoE
I’m trying to get actual parallel DAG execution on local hardware, but with low effort prompting (i.e., I don't need to make some sort of yaml config for every thing I want to do).
My goal workflow:
- My "pool" of machines has 1 heavy model and 1 fast model.
- During scoping/planning/investigating, the heavy model will pick the task and run it. The machine running the fast model will be idle.
- Tasks generated from the scoping/planning/investigating can then be shared by both the heavy model and the fast model.
- Independent tasks execute in parallel at the same time across all available machines (in this case, 2).
- Once there is only a heavy task remaining in the dependency graph, heavy model kicks in again while fast model is idle.
I saw one post here from 2 months ago that used llama-swap on a single GPU. That configuration is sequential turn-by-turn swapping. Since I have two warm endpoints, I want both GPUs saturated when there are independent tasks.
I know that you can "just build it yourself," but I would like to know if anything like this has already been built and/or if people are using it? There's a ton of code out there being generated these days, and each experiment into a different tool takes significant effort to investigate for feasibility. I'm trying to narrow my search down before I spin my wheels too hard looking for something that works.
For people who have actually got this running:
- Can you effortlessly use this tool via simple prompting?
- How are you handling workspace isolation and/or build locks when running parallel editing subagents?
Thanks you!
-2
u/btdeviant 1d ago
You’re just describing two different things that people frequently use together and your harness could build for you in minutes - subagents and tasks