Inspect the runtime and CUDA topology

Use the fhelium command-line interface to record the installed package version, inspect CUDA devices, and verify peer topology before running a benchmark or distributed workload.

Record the installed version

fhelium version

Run the command in the same environment that will import FHElium. Package version alone is not a complete native application binary interface (ABI) record; also preserve the Python, PyTorch, CUDA, driver, and GPU information reported by the environment.

Inspect CUDA devices

Print the device summary:

fhelium cuda info

Request details for one zero-based CUDA device:

fhelium cuda info --device 0

Use machine-readable output in an experiment record or admission check:

fhelium cuda info --json > results/cuda-info.json

The same device inspection is available to Python applications through the separate fhelium.native.cuda module:

from fhelium.native.cuda import get_cuda_device_properties, get_cuda_info

devices = get_cuda_device_properties()
topology = get_cuda_info(test_p2p_bandwidth=False)

A visible GPU does not establish that the installed FHElium Torch operator extension matches the runtime ABI. If import or operator loading fails, compare the complete source-build environment in the installation guide and inspect the native runtime status API.

Inspect peer topology

For a multi-GPU SPMD schedule, inspect peer-access relationships before assuming that direct device-to-device transfer is available:

fhelium cuda topo

Add the opt-in bandwidth probe only on an idle system where allocating and copying test buffers is acceptable:

fhelium cuda topo --bandwidth

Topology describes a transfer capability; it does not select a distributed schedule, partition values, or establish the ownership of cryptographic material. Use Choose a multi-GPU partition for those partitioning requirements.

Discover benchmark commands

fhelium benchmark list
fhelium benchmark --help

Running fhelium benchmark without a subcommand opens the interactive terminal interface. For reproducible automation, use a configured non-interactive subcommand and preserve structured JSON output. See Benchmark a workload correctly.