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# Contest Runners
This directory contains two self-contained contest entrypoints:
- `tools/tn_contest_runner.py`: general tensor-network path search and contraction.
- `tools/mps_contest_runner.py`: Vidal/MPS multi-node expectation runner.
Both scripts keep circuit and observable definitions inside the script so a
contest case can be edited in one place.
## Environment
Run commands from the repository root:
# TN
```bash
cd /home/yx/qibotn
```
# qibotn目录下
I_MPI_FABRICS=shm:ofi \
I_MPI_OFI_PROVIDER=tcp \
FI_PROVIDER=tcp \
CASE=main1 \
OBSERVABLES=long_z_string \
NQUBITS=34 \
NLAYERS=20 \
TORCH_THREADS=48 \
SEARCH_REPEATS=2048 \
SEARCH_TIME=300 \
SCHEDULER_HOST=10.20.1.103 \
WORKER_HOSTS="10.20.1.103 10.20.6.101" \
DASK_ADDRESS="tcp://10.20.1.103:8786" \
NWORKERS=84 \
NTHREADS=1 \
MPIEXEC_FULL="mpirun -np 4 -hostfile /home/yx/qibotn/hostfile -perhost 2" \
tools/run_tn_dask_mpi_all.sh
For Intel MPI on two nodes, use the known working style:
# 单独缩并contract计算
```bash
mpirun -np 4 -hostfile /home/yx/qibotn/hostfile -perhost 2 ...
```
Set `TCM_ENABLE=1` for CPU runs:
```bash
export TCM_ENABLE=1
```
## TN Workflow
List built-in TN contest cases:
```bash
python -u tools/tn_contest_runner.py list
```
TN path search uses dask by default. Without `--dask-address`, the script starts
a local dask cluster. For multiple servers, start one scheduler and workers
with the helper script, then pass the scheduler address to the search command.
Start the default two-node dask cluster:
```bash
cd /home/yx/qibotn
tools/manage_tn_dask_cluster.sh start
```
Check status:
```bash
cd /home/yx/qibotn
tools/manage_tn_dask_cluster.sh status
```
Stop the cluster:
```bash
cd /home/yx/qibotn
tools/manage_tn_dask_cluster.sh stop
```
The helper defaults are:
```bash
SCHEDULER_HOST=10.20.1.103
WORKER_HOSTS="10.20.1.103 10.20.1.102"
NWORKERS=48
NTHREADS=1
ROOT_DIR=/home/yx/qibotn
PYTHON_BIN=.venv/bin/python
DASK_WORKER_TTL="24 hours"
DASK_TICK_LIMIT="30 minutes"
DASK_LOST_WORKER_TIMEOUT="30 minutes"
```
Override them inline if needed:
```bash
WORKER_HOSTS="10.20.1.103 10.20.1.102" NWORKERS=48 \
tools/manage_tn_dask_cluster.sh restart
```
Check that both nodes are connected by adding `--tn-debug-trials` to a small
search. The output should include `qibotn_dask_workers` with both hosts.
`tools/tn_contest_runner.py search` stops the external dask cluster after the
search phase by default. Pass `--keep-dask` if you want to reuse the same dask
cluster for several searches.
Use enough trials to fill the cluster. With the default two-node setup there are
96 worker slots, so `--tn-search-repeats` should be at least 96. The contest
runner default is 2048.
Cotengra trials are CPU-bound and can hold the Python GIL long enough for dask
to report `Event loop was unresponsive`. Dask defaults are much more aggressive:
`scheduler.worker-ttl=5 minutes`, `admin.tick.limit=3s`, and
`deploy.lost-worker-timeout=15s`. The helper script raises these limits so
workers are not killed by dask during search. The intended timeout is
`--tn-search-time`; after that, the runner stops the external dask cluster.
Small correctness check against statevector:
```bash
python -u tools/tn_contest_runner.py validate \
--case main1 \
--nqubits 8 \
--nlayers 2 \
--torch-threads 4 \
--tn-search-repeats 8 \
--tn-search-time 5
```
Search and save contraction trees:
```bash
TCM_ENABLE=1 python -u tools/tn_contest_runner.py search \
--case main1 \
--torch-threads 48 \
--dtype complex64 \
--dask-address tcp://10.20.1.103:8786 \
--tn-search-repeats 2048 \
--tn-search-time 300
```
Contract using the saved tree on one node:
```bash
TCM_ENABLE=1 mpirun -np 2 python -u tools/tn_contest_runner.py contract \
I_MPI_FABRICS=shm:ofi \
I_MPI_OFI_PROVIDER=tcp \
FI_PROVIDER=tcp \
mpirun -np 4 -hostfile /home/yx/qibotn/hostfile -perhost 2 \
.venv/bin/python -u tools/tn_contest_runner.py contract \
--mpi \
--case main1 \
--nqubits 34 \
--nlayers 20 \
--observables long_z_string \
--tree-dir trees/contest_tn \
--torch-threads 48 \
--dtype complex64
```
Contract using the saved tree on two nodes:
```bash
TCM_ENABLE=1 mpirun -np 4 -hostfile /home/yx/qibotn/hostfile -perhost 2 \
python -u tools/tn_contest_runner.py contract \
--mpi \
--case main1 \
--torch-threads 48 \
--dtype complex64
# MPS
```
cd /home/yx/qibotn
Run search and contract in one command:
```bash
TCM_ENABLE=1 python -u tools/tn_contest_runner.py all \
--case main1 \
--torch-threads 48 \
--dtype complex64 \
--dask-address tcp://10.20.1.103:8786 \
--tn-search-repeats 2048 \
--tn-search-time 300
```
Run only selected observables:
```bash
python -u tools/tn_contest_runner.py search \
--case main2 \
--observables open_zz
```
Tree files are written to `trees/contest_tn/` by default. The tree filename
contains case, observable, qubit count, layer count, and target slice count.
If any of these change, search again.
Edit TN contest cases in `tools/tn_contest_runner.py`:
- `CASES`: case name, circuit kind, observable list, default scale.
- `build_circuit`: circuit definitions.
- `pauli_sum_observable`: observable definitions.
## MPS Workflow
List built-in Vidal/MPS contest cases:
```bash
python -u tools/mps_contest_runner.py list
```
Small correctness check against statevector:
```bash
mpirun -np 2 python -u tools/mps_contest_runner.py validate \
--case main1 \
--nqubits 8 \
--nlayers 2 \
--bond 64 \
--torch-threads 4
```
Run one MPS case on one node:
```bash
TCM_ENABLE=1 mpirun -np 2 python -u tools/mps_contest_runner.py run \
--case main1 \
--torch-threads 48
```
Run one MPS case on two nodes:
```bash
TCM_ENABLE=1 mpirun -np 4 -hostfile /home/yx/qibotn/hostfile -perhost 2 \
python -u tools/mps_contest_runner.py run \
--case main1 \
--torch-threads 48
```
Run only one observable:
```bash
TCM_ENABLE=1 mpirun -np 4 -hostfile /home/yx/qibotn/hostfile -perhost 2 \
python -u tools/mps_contest_runner.py run \
--case main1 \
--observables ring_xz \
--torch-threads 48
```
Override scale:
```bash
TCM_ENABLE=1 mpirun -np 4 -hostfile /home/yx/qibotn/hostfile -perhost 2 \
python -u tools/mps_contest_runner.py run \
--case main1 \
--nqubits 128 \
--nlayers 24 \
--bond 1024 \
--torch-threads 48
```
Edit MPS contest cases in `tools/mps_contest_runner.py`:
- `CASES`: case name, circuit kind, observable list, default scale and bond.
- `build_circuit`: circuit definitions.
- `observable`: observable definitions, including dense local terms.
## Notes
- TN uses path search plus contraction. Reuse tree files only for the exact same
circuit, observable, qubit count, layer count, seed, and slicing setup.
- TN path search defaults to dask. Use `--tn-search-backend processpool` only
for fallback/debugging.
- Prefer the default `--tn-target-size 4294967296` memory target. Do not force
`--tn-target-slices` unless you have already verified that cotengra can find
valid trees for that exact setting.
- MPS/Vidal does not use contraction-tree search. It runs the circuit directly
and reports `trunc_sum` and `trunc_max`.
- Default TN contraction is the stable torch/quimb path. Do not pass
`--tn-contract-implementation cpp` for contest runs.
I_MPI_FABRICS=shm:ofi \
I_MPI_OFI_PROVIDER=tcp \
FI_PROVIDER=tcp \
MPIEXEC_FULL="mpirun -np 4 -hostfile /home/yx/qibotn/hostfile -perhost 2" \
TORCH_THREADS=48 \
OBS_FILTER=ring_xz \
MAIN1_NQ=128 \
MAIN1_LAYERS=24 \
MAIN1_BOND=1024 \
tools/run_vidal_mpi_contest_cases.sh main1
```