Added separate dispatcher (#42)

Author: 1e-to

numba/core/cpu_dispatcher.py

@@ -6,22 +6,8 @@ class CPUDispatcher(dispatcher.Dispatcher):
     targetdescr = cpu_target
 
     def __init__(self, py_func, locals={}, targetoptions={}, impl_kind='direct', pipeline_class=compiler.Compiler):
-        if ('parallel' in targetoptions and isinstance(targetoptions['parallel'], dict) and
-                'offload' in targetoptions['parallel'] and  targetoptions['parallel']['offload'] == True):
-            import numba.dppl_config as dppl_config
-            if dppl_config.dppl_present:
-                from numba.dppl.compiler import DPPLCompiler
-                dispatcher.Dispatcher.__init__(self, py_func, locals=locals,
-                        targetoptions=targetoptions, impl_kind=impl_kind, pipeline_class=DPPLCompiler)
-            else:
-                print("---------------------------------------------------------------------------")
-                print("WARNING : offload=True option ignored. Ensure OpenCL drivers are installed.")
-                print("---------------------------------------------------------------------------")
-                dispatcher.Dispatcher.__init__(self, py_func, locals=locals,
-                    targetoptions=targetoptions, impl_kind=impl_kind, pipeline_class=pipeline_class)
-        else:
-            dispatcher.Dispatcher.__init__(self, py_func, locals=locals,
-                targetoptions=targetoptions, impl_kind=impl_kind, pipeline_class=pipeline_class)
+        dispatcher.Dispatcher.__init__(self, py_func, locals=locals,
+            targetoptions=targetoptions, impl_kind=impl_kind, pipeline_class=pipeline_class)
 
 
 dispatcher_registry['cpu'] = CPUDispatcher

numba/core/decorators.py

@@ -12,7 +12,6 @@
 from numba.stencils.stencil import stencil
 from numba.core import config, extending, sigutils, registry, cpu_dispatcher
 
-
 _logger = logging.getLogger(__name__)
 
 
@@ -151,6 +150,11 @@ def bar(x, y):
     else:
         target = options.pop('_target', 'cpu')
 
+    parallel_option = options.get('parallel')
+    if isinstance(parallel_option, dict) and parallel_option.get('offload') is True:
+        from numba.dppl import dppl_offload_dispatcher
+        target = '__dppl_offload_gpu__'
+
     options['boundscheck'] = boundscheck
 
     # Handle signature

numba/dppl/dppl_offload_dispatcher.py

@@ -0,0 +1,22 @@
+from numba.core import dispatcher, compiler
+from numba.core.registry import cpu_target, dispatcher_registry
+import numba.dppl_config as dppl_config
+
+
+class DpplOffloadDispatcher(dispatcher.Dispatcher):
+    targetdescr = cpu_target
+
+    def __init__(self, py_func, locals={}, targetoptions={}, impl_kind='direct', pipeline_class=compiler.Compiler):
+        if dppl_config.dppl_present:
+            from numba.dppl.compiler import DPPLCompiler
+            targetoptions['parallel'] = True
+            dispatcher.Dispatcher.__init__(self, py_func, locals=locals,
+                    targetoptions=targetoptions, impl_kind=impl_kind, pipeline_class=DPPLCompiler)
+        else:
+            print("---------------------------------------------------------------------")
+            print("WARNING : DPPL pipeline ignored. Ensure OpenCL drivers are installed.")
+            print("---------------------------------------------------------------------")
+            dispatcher.Dispatcher.__init__(self, py_func, locals=locals,
+                targetoptions=targetoptions, impl_kind=impl_kind, pipeline_class=pipeline_class)
+
+dispatcher_registry['__dppl_offload_gpu__'] = DpplOffloadDispatcher