---

name: rpc-deployment description: "Guides TVM RPC tracker/server/proxy setup, cross-compilation, remote module upload/load/run, and deployment troubleshooting." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

TVM RPC and Deployment

Use this route when a task involves TVM RPC, cross-compilation, remote device execution, tracker/server/proxy commands, module upload/load, target triples, remote timing, or RPC-backed meta-schedule runners.

Route

1. Confirm local TVM import and target compile support. Use ../install-build/SKILL.md for build/import failures.
2. Decide whether the task needs direct RPC server, tracker-managed devices, or a proxy. Read references/cli-and-runtime.md.
3. For cross-compilation and remote execution, read references/cross-compilation.md and keep target triple, device runtime, export artifact, upload path, and run device explicit.
4. Run scripts/rpc_cli_help_probe.py for safe CLI/API availability. It prints help text and does not start persistent services.
5. Use references/troubleshooting.md for port conflicts, keys, timeouts, tracker query failures, target-host mismatch, module load errors, and remote device availability.

API anchors

from tvm import rpc

remote = rpc.connect(url, port, key="", session_timeout=0)
tracker = rpc.connect_tracker(url, port)
remote.upload("lib.tar")
func = remote.load_module("lib.tar")
dev = remote.cpu(0)

Use rpc.LocalSession() for a local smoke that exercises upload/load/run without opening a network listener.

CLI anchors

python -m tvm.exec.rpc_server --host 0.0.0.0 --port 9090
python -m tvm.exec.rpc_tracker --host 0.0.0.0 --port 9190 --port-end 9191
python -m tvm.exec.query_rpc_tracker --host TRACKER_HOST --port 9190
python -m tvm.exec.rpc_proxy --host PROXY_HOST --port 9090 --tracker TRACKER_HOST:9190

Start long-lived services only after the user approves host/port/key choices and knows how to stop the processes.

Boundaries

• Relax compilation before export: ../relax-compile/SKILL.md.
• S-TIR/meta-schedule runner selection: ../s-tir-tuning/SKILL.md.
• TIRx CUDA kernel codegen: ../tirx-kernels/SKILL.md.