def const_array_like(ndarray):
fname = "ptx.cmem.arylike"
from .descriptor import CUDATargetDesc
aryty = CUDATargetDesc.typingctx.resolve_argument_type(ndarray)
sig = typing.signature(aryty, aryty)
return ir.Intrinsic(fname, sig, args=[ndarray])
raise NotImplementedError
[aryarg] = args
ary = aryarg.value
count = reduce(operator.mul, ary.shape)
dtype = types.from_dtype(numpy.dtype(ary.dtype))
def impl(context, args, argtys, retty):
builder = context.builder
lmod = builder.basic_block.function.module
addrspace = nvvm.ADDRSPACE_CONSTANT
data_t = dtype.llvm_as_value()
flat = ary.flatten(order='A') # preserve order
constvals = [dtype.llvm_const(flat[i]) for i in range(flat.size)]
constary = lc.Constant.array(data_t, constvals)
gv = lmod.add_global_variable(constary.type, "cmem", addrspace)
gv.linkage = lc.LINKAGE_INTERNAL
gv.global_constant = True
gv.initializer = constary
byte = lc.Type.int(8)
byte_ptr_as = lc.Type.pointer(byte, addrspace)
to_generic = nvvmutils.insert_addrspace_conv(lmod, byte, addrspace)
rawdata = builder.call(to_generic, [builder.bitcast(gv, byte_ptr_as)])
data = builder.bitcast(rawdata, lc.Type.pointer(data_t))
llintp = types.intp.llvm_as_value()
cshape = lc.Constant.array(llintp,
map(types.const_intp, ary.shape))
cstrides = lc.Constant.array(llintp,
map(types.const_intp, ary.strides))
res = lc.Constant.struct([lc.Constant.null(data.type), cshape,
cstrides])
res = builder.insert_value(res, data, 0)
return res
if ary.flags['C_CONTIGUOUS']:
contig = 'C'
elif ary.flags['F_CONTIGUOUS']:
contig = 'F'
else:
raise TypeError("array must be either C/F contiguous to be used as a "
"constant")
impl.codegen = True
impl.return_type = types.arraytype(dtype, ary.ndim, 'A')
return impl
def grid_expand(ndim):
"""grid(ndim)
ndim: [int] 1, 2 or 3
if ndim == 1:
return cuda.threadIdx.x + cuda.blockIdx.x * cuda.blockDim.x
elif ndim == 2:
x = cuda.threadIdx.x + cuda.blockIdx.x * cuda.blockDim.x
y = cuda.threadIdx.y + cuda.blockIdx.y * cuda.blockDim.y
return x, y
elif ndim == 3:
x = cuda.threadIdx.x + cuda.blockIdx.x * cuda.blockDim.x
y = cuda.threadIdx.y + cuda.blockIdx.y * cuda.blockDim.y
z = cuda.threadIdx.z + cuda.blockIdx.z * cuda.blockDim.z
return x, y, z
"""
if ndim == 1:
fname = "ptx.grid.1d"
restype = types.int32
elif ndim == 2:
fname = "ptx.grid.2d"
restype = types.UniTuple(types.int32, 2)
elif ndim == 3:
fname = "ptx.grid.3d"
restype = types.UniTuple(types.int32, 3)
else:
raise ValueError('argument can only be 1, 2, 3')
return ir.Intrinsic(fname,
typing.signature(restype, types.intp),
args=[ndim])
def local_array(shape, dtype):
shape = _legalize_shape(shape)
ndim = len(shape)
fname = "ptx.lmem.alloc"
restype = types.Array(dtype, ndim, 'C')
sig = typing.signature(restype, types.UniTuple(types.intp, ndim), types.Any)
return ir.Intrinsic(fname, sig, args=(shape, dtype))
def grid_expand(ndim):
"""grid(ndim)
Return the absolute position of the current thread in the entire
grid of blocks. *ndim* should correspond to the number of dimensions
declared when instantiating the kernel. If *ndim* is 1, a single integer
is returned. If *ndim* is 2 or 3, a tuple of the given number of
integers is returned.
Computation of the first integer is as follows::
cuda.threadIdx.x + cuda.blockIdx.x * cuda.blockDim.x
and is similar for the other two indices, but using the ``y`` and ``z``
attributes.
"""
if ndim == 1:
fname = "ptx.grid.1d"
restype = types.int32
elif ndim == 2:
fname = "ptx.grid.2d"
restype = types.UniTuple(types.int32, 2)
elif ndim == 3:
fname = "ptx.grid.3d"
restype = types.UniTuple(types.int32, 3)
else:
raise ValueError('argument can only be 1, 2, 3')
return ir.Intrinsic(fname,
typing.signature(restype, types.intp),
args=[ndim])
def gridsize_expand(ndim):
"""
Return the absolute size (or shape) in threads of the entire grid of
blocks. *ndim* should correspond to the number of dimensions declared when
instantiating the kernel.
Computation of the first integer is as follows::
cuda.blockDim.x * cuda.gridDim.x
and is similar for the other two indices, but using the ``y`` and ``z``
attributes.
"""
if ndim == 1:
fname = "ptx.gridsize.1d"
restype = types.int32
elif ndim == 2:
fname = "ptx.gridsize.2d"
restype = types.UniTuple(types.int32, 2)
elif ndim == 3:
fname = "ptx.gridsize.3d"
restype = types.UniTuple(types.int32, 3)
else:
raise ValueError('argument can only be 1, 2 or 3')
return ir.Intrinsic(fname,
typing.signature(restype, types.intp),
args=[ndim])
def _expand_non_callable_macro(self, macro, loc):
"""
Return the IR expression of expanding the non-callable macro.
"""
intr = ir.Intrinsic(macro.name, macro.func, args=())
new_expr = ir.Expr.call(func=intr, args=(), kws=(), loc=loc)
return new_expr
def expand_macros_in_block(constants, block):
calls = []
for inst in block.body:
if isinstance(inst, ir.Assign):
rhs = inst.value
if isinstance(rhs, ir.Expr) and rhs.op == 'call':
callee = rhs.func
macro = constants.get(callee.name)
if isinstance(macro, Macro):
# Rewrite calling macro
assert macro.callable
calls.append((inst, macro))
args = [constants[arg.name] for arg in rhs.args]
kws = dict((k, constants[v.name]) for k, v in rhs.kws)
result = macro.func(*args, **kws)
if result:
# Insert a new function
result.loc = rhs.loc
inst.value = ir.Expr.call(func=result, args=rhs.args,
kws=rhs.kws, loc=rhs.loc)
elif isinstance(rhs, ir.Expr) and rhs.op == 'getattr':
# Rewrite get attribute to macro call
# Non-calling macro must be triggered by get attribute
base = constants.get(rhs.value.name)
if base:
value = getattr(base, rhs.attr)
if isinstance(value, Macro):
macro = value
if not macro.callable:
intr = ir.Intrinsic(macro.name, macro.func, args=())
inst.value = ir.Expr.call(func=intr, args=(),
kws=(), loc=rhs.loc)
def const_array_like(ndarray):
fname = "ptx.cmem.arylike"
from .descriptor import CUDATargetDesc
aryty = CUDATargetDesc.typingctx.resolve_argument_type(ndarray)
sig = typing.signature(aryty, aryty)
return ir.Intrinsic(fname, sig, args=[ndarray])
def test_intrinsic(self):
a = ir.Intrinsic('foo', 'bar', (0, ), self.loc1)
b = ir.Intrinsic('foo', 'bar', (0, ), self.loc1)
c = ir.Intrinsic('foo', 'bar', (0, ), self.loc2)
d = ir.Intrinsic('baz', 'bar', (0, ), self.loc1)
e = ir.Intrinsic('foo', 'baz', (0, ), self.loc1)
f = ir.Intrinsic('foo', 'bar', (1, ), self.loc1)
self.check(a, same=[b, c], different=[d, e, f])
def local_array(shape, dtype):
ndim = 1
if isinstance(shape, tuple):
ndim = len(shape)
fname = "ptx.lmem.alloc"
restype = types.Array(dtype, ndim, 'C')
if ndim == 1:
sig = typing.signature(restype, types.intp, types.Any)
else:
sig = typing.signature(restype, types.UniTuple(types.intp, ndim),
types.Any)
return ir.Intrinsic(fname, sig, args=(shape, dtype))
def gridsize_expand(ndim):
"""gridsize(ndim)
ndim: [int] 1 or 2
if ndim == 1:
return cuda.blockDim.x * cuda.gridDim.x
elif ndim == 2:
x = cuda.blockDim.x * cuda.gridDim.x
y = cuda.blockDim.y * cuda.gridDim.y
return x, y
"""
if ndim == 1:
fname = "ptx.gridsize.1d"
restype = types.int32
elif ndim == 2:
fname = "ptx.gridsize.2d"
restype = types.UniTuple(types.int32, 2)
else:
raise ValueError('argument can only be 1 or 2')
return ir.Intrinsic(fname, typing.signature(restype, types.intp),
args=[ndim])
def expand_macros_in_block(constants, block):
'''
Performs macro expansion on a block.
Args
----
constants: dict
The pool of constants which contains the values which contains mappings
from variable names to callee names
block: ir.Block
The block to perform macro expansion on
return: bool
True if any macros were expanded
'''
expanded = False
for inst in block.body:
if isinstance(inst, ir.Assign):
rhs = inst.value
if isinstance(rhs, ir.Expr) and rhs.op == 'call':
callee = rhs.func
macro = constants.get(callee.name)
if isinstance(macro, Macro):
# Rewrite calling macro
assert macro.callable
args = [constants[arg.name] for arg in rhs.args]
kws = {}
for k, v in rhs.kws:
if v.name in constants:
kws[k] = constants[v.name]
else:
msg = "Argument {name!r} must be a " \
"constant at {loc}".format(name=k,
loc=inst.loc)
raise ValueError(msg)
try:
result = macro.func(*args, **kws)
except BaseException as e:
msg = str(e)
headfmt = "Macro expansion failed at {line}"
head = headfmt.format(line=inst.loc)
newmsg = "{0}:\n{1}".format(head, msg)
raise MacroError(newmsg)
if result:
# Insert a new function
result.loc = rhs.loc
inst.value = ir.Expr.call(func=result,
args=rhs.args,
kws=rhs.kws,
loc=rhs.loc)
expanded = True
elif isinstance(rhs, ir.Expr) and rhs.op == 'getattr':
# Rewrite get attribute to macro call
# Non-calling macro must be triggered by get attribute
base = constants.get(rhs.value.name)
if base is not None:
value = getattr(base, rhs.attr)
if isinstance(value, Macro):
macro = value
if not macro.callable:
intr = ir.Intrinsic(macro.name,
macro.func,
args=())
inst.value = ir.Expr.call(func=intr,
args=(),
kws=(),
loc=rhs.loc)
expanded = True
return expanded
