ytts/venv/lib/python3.11/site-packages/numba/cuda/intrinsics.py

from llvmlite import ir

from numba import cuda, types
from numba.core import cgutils
from numba.core.errors import RequireLiteralValue, NumbaValueError
from numba.core.typing import signature
from numba.core.extending import overload_attribute
from numba.cuda import nvvmutils
from numba.cuda.extending import intrinsic


#-------------------------------------------------------------------------------
# Grid functions

def _type_grid_function(ndim):
    val = ndim.literal_value
    if val == 1:
        restype = types.int64
    elif val in (2, 3):
        restype = types.UniTuple(types.int64, val)
    else:
        raise NumbaValueError('argument can only be 1, 2, 3')

    return signature(restype, types.int32)


@intrinsic
def grid(typingctx, 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 not isinstance(ndim, types.IntegerLiteral):
        raise RequireLiteralValue(ndim)

    sig = _type_grid_function(ndim)

    def codegen(context, builder, sig, args):
        restype = sig.return_type
        if restype == types.int64:
            return nvvmutils.get_global_id(builder, dim=1)
        elif isinstance(restype, types.UniTuple):
            ids = nvvmutils.get_global_id(builder, dim=restype.count)
            return cgutils.pack_array(builder, ids)

    return sig, codegen


@intrinsic
def gridsize(typingctx, ndim):
    '''gridsize(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. 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.blockDim.x * cuda.gridDim.x

    and is similar for the other two indices, but using the ``y`` and ``z``
    attributes.
    '''

    if not isinstance(ndim, types.IntegerLiteral):
        raise RequireLiteralValue(ndim)

    sig = _type_grid_function(ndim)

    def _nthreads_for_dim(builder, dim):
        i64 = ir.IntType(64)
        ntid = nvvmutils.call_sreg(builder, f"ntid.{dim}")
        nctaid = nvvmutils.call_sreg(builder, f"nctaid.{dim}")
        return builder.mul(builder.sext(ntid, i64), builder.sext(nctaid, i64))

    def codegen(context, builder, sig, args):
        restype = sig.return_type
        nx = _nthreads_for_dim(builder, 'x')

        if restype == types.int64:
            return nx
        elif isinstance(restype, types.UniTuple):
            ny = _nthreads_for_dim(builder, 'y')

            if restype.count == 2:
                return cgutils.pack_array(builder, (nx, ny))
            elif restype.count == 3:
                nz = _nthreads_for_dim(builder, 'z')
                return cgutils.pack_array(builder, (nx, ny, nz))

    return sig, codegen


@intrinsic
def _warpsize(typingctx):
    sig = signature(types.int32)

    def codegen(context, builder, sig, args):
        return nvvmutils.call_sreg(builder, 'warpsize')

    return sig, codegen


@overload_attribute(types.Module(cuda), 'warpsize', target='cuda')
def cuda_warpsize(mod):
    '''
    The size of a warp. All architectures implemented to date have a warp size
    of 32.
    '''
    def get(mod):
        return _warpsize()
    return get


#-------------------------------------------------------------------------------
# syncthreads

@intrinsic
def syncthreads(typingctx):
    '''
    Synchronize all threads in the same thread block.  This function implements
    the same pattern as barriers in traditional multi-threaded programming: this
    function waits until all threads in the block call it, at which point it
    returns control to all its callers.
    '''
    sig = signature(types.none)

    def codegen(context, builder, sig, args):
        fname = 'llvm.nvvm.barrier0'
        lmod = builder.module
        fnty = ir.FunctionType(ir.VoidType(), ())
        sync = cgutils.get_or_insert_function(lmod, fnty, fname)
        builder.call(sync, ())
        return context.get_dummy_value()

    return sig, codegen


def _syncthreads_predicate(typingctx, predicate, fname):
    if not isinstance(predicate, types.Integer):
        return None

    sig = signature(types.i4, types.i4)

    def codegen(context, builder, sig, args):
        fnty = ir.FunctionType(ir.IntType(32), (ir.IntType(32),))
        sync = cgutils.get_or_insert_function(builder.module, fnty, fname)
        return builder.call(sync, args)

    return sig, codegen


@intrinsic
def syncthreads_count(typingctx, predicate):
    '''
    syncthreads_count(predicate)

    An extension to numba.cuda.syncthreads where the return value is a count
    of the threads where predicate is true.
    '''
    fname = 'llvm.nvvm.barrier0.popc'
    return _syncthreads_predicate(typingctx, predicate, fname)


@intrinsic
def syncthreads_and(typingctx, predicate):
    '''
    syncthreads_and(predicate)

    An extension to numba.cuda.syncthreads where 1 is returned if predicate is
    true for all threads or 0 otherwise.
    '''
    fname = 'llvm.nvvm.barrier0.and'
    return _syncthreads_predicate(typingctx, predicate, fname)


@intrinsic
def syncthreads_or(typingctx, predicate):
    '''
    syncthreads_or(predicate)

    An extension to numba.cuda.syncthreads where 1 is returned if predicate is
    true for any thread or 0 otherwise.
    '''
    fname = 'llvm.nvvm.barrier0.or'
    return _syncthreads_predicate(typingctx, predicate, fname)