Use ninja to speed up build

op_builder/builder.py

@@ -453,9 +453,10 @@ def deepspeed_src_path(self, code_path):
 
     def builder(self):
         from torch.utils.cpp_extension import CppExtension
+        include_dirs = [os.path.abspath(x) for x in self.strip_empty_entries(self.include_paths())]
         return CppExtension(name=self.absolute_name(),
                             sources=self.strip_empty_entries(self.sources()),
-                            include_dirs=self.strip_empty_entries(self.include_paths()),
+                            include_dirs=include_dirs,
                             extra_compile_args={'cxx': self.strip_empty_entries(self.cxx_args())},
                             extra_link_args=self.strip_empty_entries(self.extra_ldflags()))
 
@@ -638,7 +639,7 @@ def builder(self):
             from torch.utils.cpp_extension import CppExtension as ExtensionBuilder
         else:
             from torch.utils.cpp_extension import CUDAExtension as ExtensionBuilder
-
+        include_dirs = [os.path.abspath(x) for x in self.strip_empty_entries(self.include_paths())]
         compile_args = {'cxx': self.strip_empty_entries(self.cxx_args())} if self.build_for_cpu else \
                        {'cxx': self.strip_empty_entries(self.cxx_args()), \
                         'nvcc': self.strip_empty_entries(self.nvcc_args())}
@@ -651,7 +652,7 @@ def builder(self):
 
         cuda_ext = ExtensionBuilder(name=self.absolute_name(),
                                     sources=self.strip_empty_entries(self.sources()),
-                                    include_dirs=self.strip_empty_entries(self.include_paths()),
+                                    include_dirs=include_dirs,
                                     libraries=self.strip_empty_entries(self.libraries_args()),
                                     extra_compile_args=compile_args,
                                     extra_link_args=self.strip_empty_entries(self.extra_ldflags()))
@@ -702,11 +703,18 @@ def nvcc_args(self):
                 '-DROCM_VERSION_MINOR=%s' % ROCM_MINOR
             ]
         else:
+            try:
+                nvcc_threads = int(os.getenv("DS_NVCC_THREADS", ""))
+                if nvcc_threads <= 0:
+                    raise ValueError("")
+            except ValueError:
+                nvcc_threads = min(os.cpu_count(), 8)
+
             cuda_major, _ = installed_cuda_version()
             args += [
                 '-allow-unsupported-compiler' if sys.platform == "win32" else '', '--use_fast_math',
                 '-std=c++17' if cuda_major > 10 else '-std=c++14', '-U__CUDA_NO_HALF_OPERATORS__',
-                '-U__CUDA_NO_HALF_CONVERSIONS__', '-U__CUDA_NO_HALF2_OPERATORS__'
+                '-U__CUDA_NO_HALF_CONVERSIONS__', '-U__CUDA_NO_HALF2_OPERATORS__', f'--threads={nvcc_threads}'
             ]
             if os.environ.get('DS_DEBUG_CUDA_BUILD', '0') == '1':
                 args.append('--ptxas-options=-v')

op_builder/cpu/builder.py

@@ -3,6 +3,8 @@
 
 # DeepSpeed Team
 
+import os
+
 try:
     # is op_builder from deepspeed or a 3p version? this should only succeed if it's deepspeed
     # if successful this also means we're doing a local install and not JIT compile path
@@ -16,12 +18,12 @@ class CPUOpBuilder(OpBuilder):
 
     def builder(self):
         from torch.utils.cpp_extension import CppExtension as ExtensionBuilder
-
+        include_dirs = [os.path.abspath(x) for x in self.strip_empty_entries(self.include_paths())]
         compile_args = {'cxx': self.strip_empty_entries(self.cxx_args())}
 
         cpp_ext = ExtensionBuilder(name=self.absolute_name(),
                                    sources=self.strip_empty_entries(self.sources()),
-                                   include_dirs=self.strip_empty_entries(self.include_paths()),
+                                   include_dirs=include_dirs,
                                    libraries=self.strip_empty_entries(self.libraries_args()),
                                    extra_compile_args=compile_args)
 

op_builder/hpu/builder.py

@@ -4,6 +4,8 @@
 
 # DeepSpeed Team
 
+import os
+
 try:
     # is op_builder from deepspeed or a 3p version? this should only succeed if it's deepspeed
     # if successful this also means we're doing a local install and not JIT compile path
@@ -17,12 +19,12 @@ class CPUOpBuilder(OpBuilder):
 
     def builder(self):
         from torch.utils.cpp_extension import CppExtension as ExtensionBuilder
-
+        include_dirs = [os.path.abspath(x) for x in self.strip_empty_entries(self.include_paths())]
         compile_args = {'cxx': self.strip_empty_entries(self.cxx_args())}
 
         cpp_ext = ExtensionBuilder(name=self.absolute_name(),
                                    sources=self.strip_empty_entries(self.sources()),
-                                   include_dirs=self.strip_empty_entries(self.include_paths()),
+                                   include_dirs=include_dirs,
                                    libraries=self.strip_empty_entries(self.libraries_args()),
                                    extra_compile_args=compile_args)
 

op_builder/inference_core_ops.py

@@ -60,13 +60,13 @@ def sources(self):
         sources = [
             "inference/v2/kernels/core_ops/core_ops.cpp",
             "inference/v2/kernels/core_ops/bias_activations/bias_activation.cpp",
-            "inference/v2/kernels/core_ops/bias_activations/bias_activation.cu",
+            "inference/v2/kernels/core_ops/bias_activations/bias_activation_cuda.cu",
             "inference/v2/kernels/core_ops/cuda_layer_norm/layer_norm.cpp",
-            "inference/v2/kernels/core_ops/cuda_layer_norm/layer_norm.cu",
+            "inference/v2/kernels/core_ops/cuda_layer_norm/layer_norm_cuda.cu",
             "inference/v2/kernels/core_ops/cuda_rms_norm/rms_norm.cpp",
-            "inference/v2/kernels/core_ops/cuda_rms_norm/rms_norm.cu",
+            "inference/v2/kernels/core_ops/cuda_rms_norm/rms_norm_cuda.cu",
             "inference/v2/kernels/core_ops/gated_activations/gated_activation_kernels.cpp",
-            "inference/v2/kernels/core_ops/gated_activations/gated_activation_kernels.cu",
+            "inference/v2/kernels/core_ops/gated_activations/gated_activation_kernels_cuda.cu",
         ]
 
         prefix = self.get_prefix()

op_builder/ragged_ops.py

@@ -63,18 +63,18 @@ def sources(self):
             "inference/v2/kernels/ragged_ops/atom_builder/atom_builder.cpp",
             "inference/v2/kernels/ragged_ops/blocked_flash/blocked_flash.cpp",
             "inference/v2/kernels/ragged_ops/embed/embed.cpp",
-            "inference/v2/kernels/ragged_ops/embed/embed.cu",
+            "inference/v2/kernels/ragged_ops/embed/embed_cuda.cu",
             "inference/v2/kernels/ragged_ops/linear_blocked_kv_rotary/blocked_kv_rotary.cpp",
-            "inference/v2/kernels/ragged_ops/linear_blocked_kv_rotary/blocked_kv_rotary.cu",
+            "inference/v2/kernels/ragged_ops/linear_blocked_kv_rotary/blocked_kv_rotary_cuda.cu",
             "inference/v2/kernels/ragged_ops/logits_gather/logits_gather.cpp",
-            "inference/v2/kernels/ragged_ops/logits_gather/logits_gather.cu",
+            "inference/v2/kernels/ragged_ops/logits_gather/logits_gather_cuda.cu",
             "inference/v2/kernels/ragged_ops/moe_scatter/moe_scatter.cpp",
-            "inference/v2/kernels/ragged_ops/moe_scatter/moe_scatter.cu",
+            "inference/v2/kernels/ragged_ops/moe_scatter/moe_scatter_cuda.cu",
             "inference/v2/kernels/ragged_ops/moe_gather/moe_gather.cpp",
-            "inference/v2/kernels/ragged_ops/moe_gather/moe_gather.cu",
+            "inference/v2/kernels/ragged_ops/moe_gather/moe_gather_cuda.cu",
             "inference/v2/kernels/ragged_ops/ragged_helpers/ragged_kernel_helpers.cpp",
             "inference/v2/kernels/ragged_ops/top_k_gating/top_k_gating.cpp",
-            "inference/v2/kernels/ragged_ops/top_k_gating/top_k_gating.cu",
+            "inference/v2/kernels/ragged_ops/top_k_gating/top_k_gating_cuda.cu",
         ]
 
         prefix = self.get_prefix()

op_builder/xpu/builder.py

@@ -23,11 +23,11 @@ def builder(self):
             from intel_extension_for_pytorch.xpu.cpp_extension import DPCPPExtension
         except ImportError:
             from intel_extension_for_pytorch.xpu.utils import DPCPPExtension
-
+        include_dirs = [os.path.abspath(x) for x in self.strip_empty_entries(self.include_paths())]
         print("dpcpp sources = {}".format(self.sources()))
         dpcpp_ext = DPCPPExtension(name=self.absolute_name(),
                                    sources=self.strip_empty_entries(self.sources()),
-                                   include_dirs=self.strip_empty_entries(self.include_paths()),
+                                   include_dirs=include_dirs,
                                    extra_compile_args={
                                        'cxx': self.strip_empty_entries(self.cxx_args()),
                                    },

setup.py

@@ -119,7 +119,8 @@ def get_env_if_set(key, default: typing.Any = ""):
 # For any pre-installed ops force disable ninja.
 if torch_available:
     from accelerator import get_accelerator
-    cmdclass['build_ext'] = get_accelerator().build_extension().with_options(use_ninja=False)
+    use_ninja = not is_env_set("DS_DISABLE_NINJA")
+    cmdclass['build_ext'] = get_accelerator().build_extension().with_options(use_ninja=use_ninja)
 
 if torch_available:
     TORCH_MAJOR = torch.__version__.split('.')[0]