Ejemplo n.º 1
0
def run_test():
    size = 10
    weight_array = WeightArray(
        np.ones((3, 3), dtype=np.float) / 9
    )
    component = StencilComponent(
        "input",
        weight_array
    )
    red = DomainUnion([
        RectangularDomain((
            (1, -1, 2),
            (1, -1, 2)
        )),
        RectangularDomain((
            (2, 0, 2),
            (2, 0, 2)
        ))
    ])
    stencil = Stencil(
        component,
        "output",
        red
    )
    ccompiler = CCompiler()
    kern = ccompiler.compile(stencil)
    arr = np.arange(size**2, dtype=np.float).reshape((size, size))
    out = np.zeros_like(arr)
    kern(out, arr)
    print(out)
Ejemplo n.º 2
0
def test(tile_size, n):
    opt_args = [test_in] + [test_in]*NDIM + [test_opt_out]
    compiler = CCompiler()
    compiler.tile_size = tile_size
    optimized = analyzer.repackage(sten, NDIM, n)
    kern = compiler.compile(optimized)
    kern(*opt_args)
    t = -time.time()
    kern(*opt_args)
    t += time.time()
    print(tile_size, n, t/ITER)
Ejemplo n.º 3
0
def run_test():
    weight_array = WeightArray(
        np.ones((3, 3, 3), dtype=np.float) / 27
    )
    component = StencilComponent(
        "input",
        weight_array
    )
    stencil = Stencil(
        component,
        "output",
        [(1, -1, 1)]*3
    )
    ccompiler = CCompiler()
    kern = ccompiler.compile(stencil)
    arr = np.arange(66**3, dtype=np.float).reshape((66, 66, 66))
    out = np.zeros_like(arr)
    kern(out, arr)
Ejemplo n.º 4
0
    upper_diff *= StencilComponent("beta_{}".format(dim),
                                 SparseWeightArray({Vector.unit_vector(dim, ndim): 1}))

    return lower_diff + upper_diff


def create_stencil(ndim):
    components = [create_component(ndim, dim) for dim in range(ndim)] ## creates components for beta_1 to beta_n
    total = sum(components)
    return Stencil(total, "out", [(1, -1, 1)]*ndim, "mesh")

sten = create_stencil(NDIM)

optimized = analyzer.repackage(sten, NDIM, DECOMP)

naive_compiler = CCompiler()

optimized_compiler = CCompiler()

naive_kernel = naive_compiler.compile(StencilGroup([sten]*ITER))
optimized_kernel = optimized_compiler.compile(StencilGroup(optimized.body*ITER))

test_in = np.arange((SIZE + 2)**NDIM, dtype=np.float).reshape((SIZE+2,)*NDIM)

test_out = np.zeros_like(test_in)
test_opt_out = np.zeros_like(test_in)

naive_args = [test_in] + [test_in]*NDIM + [test_out]
naive_kernel(*naive_args)

t = -time.time()