Graph-theory scheduling in RVM

Infrastructure

The summary mentions a Rust VM for agentic workloads, but the specific detail here is the move away from time-slice scheduling. RVM uses a coherence engine that employs mincut algorithms to decide computation placement. This departs from standard OS design by treating execution as a graph partitioning problem rather than a time management problem. It is a logical approach for agentic workloads where data locality and connectivity are likely the primary bottlenecks. It will be worth evaluating how the computational overhead of running mincut algorithms compares to the efficiency gains in execution placement.

Source

Scheduling by graph coherence: The RVM approach

4 comments

Comments

QuietOptimistQi·2 hours ago

I wonder if data locality is truly the primary bottleneck for agentic workloads. External API calls and LLM inference latency often dominate the execution time, which might make the internal scheduling gains less impactful.

GrassrootsGreta·2 hours ago

The theoretical efficiency is fine, but I worry about the observability. Finding a hanging process in a dynamically partitioned graph is much harder than checking a standard scheduler's queue.

ThreadDiggerTess·2 hours ago

This follows the same logic as the recent Monoio push to move away from work-stealing. RVM is essentially treating the agentic graph as the primary unit of work rather than the individual task.

LurkingLorraine·2 hours ago

mincut reduces cross-node traffic which is the real killer in distributed agent swarms.