Configure debugging environment#

  1. Activate the debugger and compiler:

    export ONEAPI_ROOT=/path/to/oneapi
source $ONEAPI_ROOT/debugger/latest/env/vars.sh
source $ONEAPI_ROOT/compiler/latest/env/vars.sh

  2. Create and activate conda environment with the installed numba-dpex:

    conda create numba-dpex-dev numba-dpex
conda activate numba-dpex-dev

  3. Activate NEO drivers (optional).

    If you want to use the local NEO driver, activate the variables for it. See the NEO driver.

  4. Check debugging environment.

    You can check the correctness of the work with the following example:

     5import dpctl
 6import dpnp as np
 7
 8import numba_dpex as ndpx
 9
10
11@ndpx.kernel(debug=True)
12def data_parallel_sum(a, b, c):
13    i = ndpx.get_global_id(0)
14    c[i] = a[i] + b[i]  # Condition breakpoint location
15
16
17global_size = 10
18N = global_size
19
20a = np.array(np.random.random(N), dtype=np.float32)
21b = np.array(np.random.random(N), dtype=np.float32)
22c = np.ones_like(a)
23
24data_parallel_sum[ndpx.Range(global_size)](a, b, c)
25
26print("Done...")

    Launch the Intel® Distribution for GDB* and set a breakpoint in the kernel:

    $ gdb-oneapi -q --args python simple_sum.py
(gdb) break simple_sum.py:22
No source file named simple_sum.py.
Make breakpoint pending on future shared library load? (y or [n]) y
Breakpoint 1 (simple_sum.py:22) pending.
(gdb) run

    In the output you can see that the breakpoint was hit successfully:

    Thread 2.2 hit Breakpoint 1, with SIMD lanes [0-7], __main__::data_parallel_sum () at simple_sum.py:22
22           i = dpex.get_global_id(0)
(gdb) continue
Done...
...