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:

   import dpnp as np
   
   import numba_dpex as ndpx
   
   
   @ndpx.kernel(debug=True)
   def data_parallel_sum(item, a, b, c):
       i = item.get_id(0)
       c[i] = a[i] + b[i]  # Condition breakpoint location
   
   
   global_size = 10
   N = global_size
   
   a = np.array(np.random.random(N), dtype=np.float32)
   b = np.array(np.random.random(N), dtype=np.float32)
   c = np.ones_like(a)
   
   ndpx.call_kernel(data_parallel_sum, ndpx.Range(global_size), a, b, c)
   
   print("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...
   ...