def __call__(self, definition_ir) -> Dict[str, Dict[str, str]]:
gtir = GtirPipeline(DefIRToGTIR.apply(definition_ir)).full()
base_oir = gtir_to_oir.GTIRToOIR().visit(gtir)
oir_pipeline = self.backend.builder.options.backend_opts.get(
"oir_pipeline", DefaultPipeline(skip=[FillFlushToLocalKCaches]))
oir = oir_pipeline.run(base_oir)
gtcpp = oir_to_gtcpp.OIRToGTCpp().visit(oir)
format_source = self.backend.builder.options.format_source
implementation = gtcpp_codegen.GTCppCodegen.apply(
gtcpp,
gt_backend_t=self.backend.GT_BACKEND_T,
format_source=format_source)
bindings = GTCppBindingsCodegen.apply(gtcpp,
module_name=self.module_name,
backend=self.backend,
format_source=format_source)
bindings_ext = ".cu" if self.backend.GT_BACKEND_T == "gpu" else ".cpp"
return {
"computation": {
"computation.hpp": implementation
},
"bindings": {
"bindings" + bindings_ext: bindings
},
}
def __call__(
self,
definition_ir: StencilDefinition) -> Dict[str, Dict[str, str]]:
gtir = GtirPipeline(DefIRToGTIR.apply(definition_ir)).full()
base_oir = gtir_to_oir.GTIRToOIR().visit(gtir)
oir_pipeline = self.backend.builder.options.backend_opts.get(
"oir_pipeline",
DefaultPipeline(skip=[MaskStmtMerging, MaskInlining]),
)
oir = oir_pipeline.run(base_oir)
sdfg = OirSDFGBuilder().visit(oir)
sdfg.expand_library_nodes(recursive=True)
sdfg.apply_strict_transformations(validate=True)
implementation = DaCeComputationCodegen.apply(gtir, sdfg)
bindings = DaCeBindingsCodegen.apply(gtir,
sdfg,
module_name=self.module_name,
backend=self.backend)
bindings_ext = ".cu" if self.backend.GT_BACKEND_T == "gpu" else ".cpp"
return {
"computation": {
"computation.hpp": implementation
},
"bindings": {
"bindings" + bindings_ext: bindings
},
}
def __call__(self, definition_ir) -> Dict[str, Dict[str, str]]:
gtir = GtirPipeline(DefIRToGTIR.apply(definition_ir)).full()
base_oir = gtir_to_oir.GTIRToOIR().visit(gtir)
oir_pipeline = self.backend.builder.options.backend_opts.get(
"oir_pipeline", DefaultPipeline(skip=[NoFieldAccessPruning]))
oir = oir_pipeline.run(base_oir)
oir = FillFlushToLocalKCaches().visit(oir)
cuir = oir_to_cuir.OIRToCUIR().visit(oir)
cuir = kernel_fusion.FuseKernels().visit(cuir)
cuir = extent_analysis.CacheExtents().visit(cuir)
format_source = self.backend.builder.options.format_source
implementation = cuir_codegen.CUIRCodegen.apply(
cuir, format_source=format_source)
bindings = GTCCudaBindingsCodegen.apply(cuir,
module_name=self.module_name,
backend=self.backend,
format_source=format_source)
return {
"computation": {
"computation.hpp": implementation
},
"bindings": {
"bindings.cu": bindings
},
}
def __call__(
self,
definition_ir: StencilDefinition) -> Dict[str, Dict[str, str]]:
gtir = DefIRToGTIR.apply(definition_ir)
gtir_without_unused_params = prune_unused_parameters(gtir)
dtype_deduced = resolve_dtype(gtir_without_unused_params)
upcasted = upcast(dtype_deduced)
oir = gtir_to_oir.GTIRToOIR().visit(upcasted)
oir = self._optimize_oir(oir)
sdfg = OirSDFGBuilder().visit(oir)
sdfg.expand_library_nodes(recursive=True)
# TODO uncomment once the branch dace/linus-fixes-8 is merged into dace/master
# sdfg.apply_strict_transformations(validate=True) # noqa: E800 Found commented out code
implementation = DaCeComputationCodegen.apply(gtir, sdfg)
bindings = DaCeBindingsCodegen.apply(gtir,
sdfg,
module_name=self.module_name)
bindings_ext = ".cu" if self.backend.GT_BACKEND_T == "gpu" else ".cpp"
return {
"computation": {
"computation.hpp": implementation
},
"bindings": {
"bindings" + bindings_ext: bindings
},
}
def stencil_def_to_oir(stencil_def, externals):
build_options = BuildOptions(
name=stencil_def.__name__, module=__name__, rebuild=True, backend_opts={}, build_info=None
)
definition_ir = GTScriptFrontend.generate(
stencil_def, externals=externals, options=build_options
)
gtir = GtirPipeline(DefIRToGTIR.apply(definition_ir)).full()
return GTIRToOIR().visit(gtir)
def __call__(self, definition_ir) -> Dict[str, Dict[str, str]]:
gtir = DefIRToGTIR.apply(definition_ir)
gtir_without_unused_params = prune_unused_parameters(gtir)
dtype_deduced = resolve_dtype(gtir_without_unused_params)
upcasted = upcast(dtype_deduced)
oir = gtir_to_oir.GTIRToOIR().visit(upcasted)
oir = self._optimize_oir(oir)
cuir = oir_to_cuir.OIRToCUIR().visit(oir)
cuir = kernel_fusion.FuseKernels().visit(cuir)
cuir = extent_analysis.ComputeExtents().visit(cuir)
cuir = extent_analysis.CacheExtents().visit(cuir)
implementation = cuir_codegen.CUIRCodegen.apply(cuir)
bindings = GTCCudaBindingsCodegen.apply(cuir, module_name=self.module_name)
return {
"computation": {"computation.hpp": implementation},
"bindings": {"bindings.cu": bindings},
}
def __call__(self, definition_ir) -> Dict[str, Dict[str, str]]:
gtir = GtirPipeline(DefIRToGTIR.apply(definition_ir)).full()
oir = gtir_to_oir.GTIRToOIR().visit(gtir)
oir = self._optimize_oir(oir)
gtcpp = oir_to_gtcpp.OIRToGTCpp().visit(oir)
implementation = gtcpp_codegen.GTCppCodegen.apply(
gtcpp, gt_backend_t=self.gt_backend_t)
bindings = GTCppBindingsCodegen.apply(gtcpp,
module_name=self.module_name,
gt_backend_t=self.gt_backend_t)
bindings_ext = ".cu" if self.gt_backend_t == "gpu" else ".cpp"
return {
"computation": {
"computation.hpp": implementation
},
"bindings": {
"bindings" + bindings_ext: bindings
},
}
def __call__(self, definition_ir) -> Dict[str, Dict[str, str]]:
gtir = GtirPipeline(DefIRToGTIR.apply(definition_ir)).full()
oir = OirPipeline(gtir_to_oir.GTIRToOIR().visit(gtir)).full(
skip=[FillFlushToLocalKCaches])
gtcpp = oir_to_gtcpp.OIRToGTCpp().visit(oir)
implementation = gtcpp_codegen.GTCppCodegen.apply(
gtcpp, gt_backend_t=self.backend.GT_BACKEND_T)
bindings = GTCppBindingsCodegen.apply(gtcpp,
module_name=self.module_name,
backend=self.backend)
bindings_ext = ".cu" if self.backend.GT_BACKEND_T == "gpu" else ".cpp"
return {
"computation": {
"computation.hpp": implementation
},
"bindings": {
"bindings" + bindings_ext: bindings
},
}
def __call__(self, definition_ir) -> Dict[str, Dict[str, str]]:
gtir = GtirPipeline(DefIRToGTIR.apply(definition_ir)).full()
oir = OirPipeline(gtir_to_oir.GTIRToOIR().visit(gtir)).full(
skip=[NoFieldAccessPruning])
cuir = oir_to_cuir.OIRToCUIR().visit(oir)
cuir = kernel_fusion.FuseKernels().visit(cuir)
cuir = extent_analysis.ComputeExtents().visit(cuir)
cuir = extent_analysis.CacheExtents().visit(cuir)
implementation = cuir_codegen.CUIRCodegen.apply(cuir)
bindings = GTCCudaBindingsCodegen.apply(cuir,
module_name=self.module_name,
backend=self.backend)
return {
"computation": {
"computation.hpp": implementation
},
"bindings": {
"bindings.cu": bindings
},
}
def __call__(self, definition_ir) -> Dict[str, Dict[str, str]]:
gtir = DefIRToGTIR.apply(definition_ir)
gtir_without_unused_params = prune_unused_parameters(gtir)
dtype_deduced = resolve_dtype(gtir_without_unused_params)
upcasted = upcast(dtype_deduced)
oir = gtir_to_oir.GTIRToOIR().visit(upcasted)
oir = self._optimize_oir(oir)
gtcpp = oir_to_gtcpp.OIRToGTCpp().visit(oir)
implementation = gtcpp_codegen.GTCppCodegen.apply(
gtcpp, gt_backend_t=self.gt_backend_t)
bindings = GTCppBindingsCodegen.apply(gtcpp,
module_name=self.module_name,
gt_backend_t=self.gt_backend_t)
bindings_ext = ".cu" if self.gt_backend_t == "gpu" else ".cpp"
return {
"computation": {
"computation.hpp": implementation
},
"bindings": {
"bindings" + bindings_ext: bindings
},
}
def gtir_pipeline(self) -> GtirPipeline:
return self._build_data.get(
"gtir_pipeline") or self._build_data.setdefault(
"gtir_pipeline",
GtirPipeline(DefIRToGTIR.apply(self.definition_ir)))
