132 lines
4.5 KiB
Python
132 lines
4.5 KiB
Python
#!/usr/bin/env python
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#
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# ***** BEGIN GPL LICENSE BLOCK *****
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#
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# This program is free software; you can redistribute it and/or
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# modify it under the terms of the GNU General Public License
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# as published by the Free Software Foundation; either version 2
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# of the License, or (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License
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# along with this program; if not, write to the Free Software Foundation,
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# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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#
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# The Original Code is Copyright (C) 2011, Blender Foundation
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# All rights reserved.
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#
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# The Original Code is: all of this file.
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#
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# Contributor(s): Nathan Letwory.
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#
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# ***** END GPL LICENSE BLOCK *****
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import re
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import subprocess
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import sys
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import os
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import Blender as B
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def normpath(path):
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return os.path.abspath(os.path.normpath(path))
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Import ('env')
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kernel_binaries = []
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#Bitness
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if B.bitness == 32:
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bits = 32
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else:
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bits = 64
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if env['WITH_BF_CYCLES_CUDA_BINARIES']:
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kernel = env.Clone()
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# cuda info
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nvcc = env['BF_CYCLES_CUDA_NVCC']
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cuda_archs = env['BF_CYCLES_CUDA_BINARIES_ARCH']
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# build directory
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root_build_dir = normpath(env['BF_BUILDDIR'])
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build_dir = os.path.join(root_build_dir, 'intern/cycles/kernel')
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# source directories and files
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source_dir = Dir('.').srcnode().path
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kernel_file = os.path.join(source_dir, "kernel.cu")
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util_dir = os.path.join(source_dir, "../util")
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svm_dir = os.path.join(source_dir, "../svm")
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closure_dir = os.path.join(source_dir, "../closure")
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# get CUDA version
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nvcc_pipe = subprocess.Popen([nvcc, "--version"],stdout=subprocess.PIPE,stderr=subprocess.PIPE)
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output, erroroutput = nvcc_pipe.communicate()
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cuda_major_minor = re.findall(r'release (\d+).(\d+)', output)[0]
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cuda_version = int(cuda_major_minor[0])*10 + int(cuda_major_minor[1])
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if cuda_version != 50:
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print("CUDA version %d.%d detected, build may succeed but only CUDA 5.0 is officially supported." % (cuda_version/10, cuda_version%10))
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# nvcc flags
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nvcc_flags = "-m%s" % (bits)
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nvcc_flags += " --cubin --ptxas-options=\"-v\""
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nvcc_flags += " -D__KERNEL_CUDA_VERSION__=%d" % (cuda_version)
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nvcc_flags += " -DCCL_NAMESPACE_BEGIN= -DCCL_NAMESPACE_END= -DNVCC"
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nvcc_flags += " -I \"%s\" -I \"%s\" -I \"%s\"" % (util_dir, svm_dir, closure_dir)
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# dependencies
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dependencies = ['kernel.cu'] + kernel.Glob('*.h') + kernel.Glob('../util/*.h') + kernel.Glob('svm/*.h') + kernel.Glob('closure/*.h')
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last_cubin_file = None
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# add command for each cuda architecture
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for arch in cuda_archs:
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cubin_file = os.path.join(build_dir, "kernel_%s.cubin" % arch)
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# build flags depending on CUDA version and arch
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if cuda_version < 50:
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if arch == "sm_35":
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print("Can't build kernel for CUDA sm_35 architecture, skipping")
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continue
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# CUDA 4.x
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if arch.startswith("sm_1"):
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# sm_1x
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cuda_arch_flags = "--maxrregcount=24 --opencc-options -OPT:Olimit=0"
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elif arch.startswith("sm_2"):
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# sm_2x
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cuda_arch_flags = "--maxrregcount=24"
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else:
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# sm_3x
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cuda_arch_flags = "--maxrregcount=32"
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else:
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# CUDA 5.x
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if arch.startswith("sm_1"):
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# sm_1x
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cuda_arch_flags = "--maxrregcount=24 --opencc-options -OPT:Olimit=0 --use_fast_math"
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elif arch.startswith("sm_2"):
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# sm_2x
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cuda_arch_flags = "--maxrregcount=32 --use_fast_math"
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else:
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# sm_3x
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cuda_arch_flags = "--maxrregcount=32 --use_fast_math"
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command = "\"%s\" -arch=%s %s %s \"%s\" -o \"%s\"" % (nvcc, arch, nvcc_flags, cuda_arch_flags, kernel_file, cubin_file)
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kernel.Command(cubin_file, 'kernel.cu', command)
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kernel.Depends(cubin_file, dependencies)
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kernel_binaries.append(cubin_file)
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if not env['WITH_BF_CYCLES_CUDA_THREADED_COMPILE']:
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# trick to compile one kernel at a time to reduce memory usage
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if last_cubin_file:
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kernel.Depends(cubin_file, last_cubin_file)
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last_cubin_file = cubin_file
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Return('kernel_binaries')
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