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