Commit a57a164a authored by Stephan Seitz's avatar Stephan Seitz
Browse files

llvm: Mark CUDA kernels and load/call resulting ptx with pycuda

parent 2e6f3efe
......@@ -13,6 +13,24 @@ from pystencils.data_types import (
from pystencils.llvm.control_flow import Loop
# From Numba
def set_cuda_kernel(lfunc):
from llvmlite.llvmpy.core import MetaData, MetaDataString, Constant, Type
m = lfunc.module
ops = lfunc, MetaDataString.get(m, "kernel"), Constant.int(Type.int(), 1)
md = MetaData.get(m, ops)
nmd = m.get_or_insert_named_metadata('nvvm.annotations')
nmd.add(md)
# set nvvm ir version
i32 = ir.IntType(32)
md_ver = m.add_metadata([i32(1), i32(2), i32(2), i32(0)])
m.add_named_metadata('nvvmir.version', md_ver)
# From Numba
def _call_sreg(builder, name):
module = builder.module
......@@ -191,6 +209,9 @@ class LLVMPrinter(Printer):
self._print(func.body)
self.builder.ret_void()
self.fn = fn
if self.target == 'gpu':
set_cuda_kernel(fn)
return fn
def _print_Block(self, block):
......
import ctypes as ct
import subprocess
from functools import partial
from itertools import chain
from os.path import exists, join
import llvmlite.binding as llvm
......@@ -103,9 +105,9 @@ def generate_and_jit(ast):
target = 'gpu' if ast._backend == 'llvm_gpu' else 'cpu'
gen = generate_llvm(ast, target=target)
if isinstance(gen, ir.Module):
return compile_llvm(gen, target)
return compile_llvm(gen, target, ast)
else:
return compile_llvm(gen.module, target)
return compile_llvm(gen.module, target, ast)
def make_python_function(ast, argument_dict={}, func=None):
......@@ -120,8 +122,8 @@ def make_python_function(ast, argument_dict={}, func=None):
return lambda: func(*args)
def compile_llvm(module, target='cpu'):
jit = CudaJit() if target == "gpu" else Jit()
def compile_llvm(module, target='cpu', ast=None):
jit = CudaJit(ast) if target == "gpu" else Jit()
jit.parse(module)
jit.optimize()
jit.compile()
......@@ -243,12 +245,13 @@ class CudaJit(Jit):
default_data_layout = data_layout[MACHINE_BITS]
def __init__(self):
def __init__(self, ast):
# super().__init__()
# self.target = llvm.Target.from_triple(self.CUDA_TRIPLE[self.MACHINE_BITS])
self._data_layout = self.default_data_layout[self.MACHINE_BITS]
# self._target_data = llvm.create_target_data(self._data_layout)
self.indexing = ast.indexing
def optimize(self):
pmb = llvm.create_pass_manager_builder()
......@@ -278,7 +281,6 @@ class CudaJit(Jit):
llvmmod.verify()
llvmmod.name = 'module'
self.module = str(llvmmod)
self._llvmmod = llvm.parse_assembly(str(llvmmod))
def compile(self):
......@@ -287,48 +289,30 @@ class CudaJit(Jit):
compiler_cache = get_cache_config()['object_cache']
ir_file = join(compiler_cache, hashlib.md5(str(self._llvmmod).encode()).hexdigest() + '.ll')
ptx_file = ir_file.replace('.ll', '.ptx')
try:
from pycuda.driver import Context
arch = "sm_%d%d" % Context.get_device().compute_capability()
except Exception:
arch = "sm_35"
if not exists(ptx_file):
self.write_ll(ir_file)
try:
from pycuda.driver import Context
arch = "sm_%d%d" % Context.get_device().compute_capability()
except Exception:
arch = "sm_35"
subprocess.check_call(['llc-10', '-mcpu=' + arch, ir_file, '-o', ptx_file])
# TODO: make loading of ptx work
# import pycuda.autoinit
# def handler(compile_success_bool, info_str, error_str):
# if not compile_success_bool:
# print(info_str)
# print(error_str)
# cubin_file = ir_file.replace('.ll', '.cubin')
# if not exists(cubin_file):
# subprocess.check_call(['ptxas', '--gpu-name', arch, ptx_file, '-o', cubin_file])
import pycuda.driver
# # with open(ptx_file, 'rb') as f:
# # ptx_code = f.read()
# # from pycuda.driver import jit_input_type
# # self.linker.add_data(ptx_code, jit_input_type.PTX, 'foo')
# from pycuda.compiler import DynamicModule
# from pycuda.driver import jit_input_type
# module = DynamicModule().add_file(ptx_file, jit_input_type.PTX)
# module.link()
# # cuda_module = pycuda.driver.module_from_buffer(ptx_code, message_handler=handler)
# # print(dir(cuda_module))
# self.fptr = dict()
# module.get_function('kernel')
cuda_module = pycuda.driver.module_from_file(ptx_file) # also works: cubin_file
self.cuda_module = cuda_module
def __call__(self, func, *args, **kwargs):
fptr = {}
for func in self.module.functions:
if not func.is_declaration:
return_type = None
if func.ftype.return_type != ir.VoidType():
return_type = to_ctypes(create_composite_type_from_string(str(func.ftype.return_type)))
args = [ctypes_from_llvm(arg) for arg in func.ftype.args]
function_address = self.ee.get_function_address(func.name)
fptr[func.name] = ct.CFUNCTYPE(return_type, *args)(function_address)
self.fptr = fptr
shape = [a.shape for a in chain(args, kwargs.values()) if hasattr(a, 'shape')][0]
block_and_thread_numbers = self.indexing.call_parameters(shape)
block_and_thread_numbers['block'] = tuple(int(i) for i in block_and_thread_numbers['block'])
block_and_thread_numbers['grid'] = tuple(int(i) for i in block_and_thread_numbers['grid'])
self.cuda_module.get_function(func)(*args, **kwargs, **block_and_thread_numbers)
def get_function_ptr(self, name):
return partial(self._call__, name)
......@@ -33,13 +33,19 @@ def test_jacobi_fixed_field_size():
def test_jacobi_fixed_field_size_gpu():
size = (30, 20)
import pycuda.autoinit # noqa
from pycuda.gpuarray import to_gpu
src_field_llvm = np.random.rand(*size)
src_field_py = np.copy(src_field_llvm)
dst_field_llvm = np.zeros(size)
dst_field_py = np.zeros(size)
f = Field.create_from_numpy_array("f", src_field_llvm)
d = Field.create_from_numpy_array("d", dst_field_llvm)
f = Field.create_from_numpy_array("f", src_field_py)
d = Field.create_from_numpy_array("d", dst_field_py)
src_field_llvm = to_gpu(src_field_llvm)
dst_field_llvm = to_gpu(dst_field_llvm)
jacobi = Assignment(d[0, 0], (f[1, 0] + f[-1, 0] + f[0, 1] + f[0, -1]) / 4)
ast = create_kernel([jacobi], target='gpu')
......@@ -52,7 +58,7 @@ def test_jacobi_fixed_field_size_gpu():
jit = generate_and_jit(ast)
jit('kernel', dst_field_llvm, src_field_llvm)
error = np.sum(np.abs(dst_field_py - dst_field_llvm))
error = np.sum(np.abs(dst_field_py - dst_field_llvm.get()))
np.testing.assert_almost_equal(error, 0.0)
......
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