SIGSEGV in cs_sles_solve_ccc_fv when CS_CUDA_ALLOC_DEVICE_UVM is not set (v9.1.0)

[diskdog]

Description

cs_sles_solve_ccc_fv allocates its extended solver buffers using CS_ALLOC_DEVICE (device-only memory). Those buffers are subsequently passed to the CPU-side convergence check, which dereferences them on the host and causes a SIGSEGV.

Setting CS_CUDA_ALLOC_DEVICE_UVM=1 before launching the solver works around the crash: it remaps cs_alloc_mode_device to CS_ALLOC_HOST_DEVICE_SHARED at initialisation time (see cs_base_cuda.cu:777), making the buffers accessible from both host and device.

Steps to reproduce

1. Build code_saturne v9.1.0 with CUDA support.
2. Run any case that exercises the CUDA sparse linear solver (cs_sles_solve_ccc_fv) without setting CS_CUDA_ALLOC_DEVICE_UVM.
3. Observe SIGSEGV during the convergence check after the first solver call.

Workaround

export CS_CUDA_ALLOC_DEVICE_UVM=1

Set this before invoking the solver. It prevents the crash by ensuring solver buffers are in unified/shared memory.

Expected behaviour

cs_sles_solve_ccc_fv should either allocate convergence-check buffers in host-accessible memory directly, or the convergence check should use a device-to-host copy rather than a direct host dereference.

Environment

• code_saturne version: 9.1.0
• CUDA version: 13.1
• GPU architecture: sm_75
• OS: Ubuntu (x86_64)