Пример #1
0
def chunkwise_kernel():
    ast, env = compile(source)

    #Array = ca.carray(xrange(25000), rootdir='example1', mode='w',
                #dtype='int32', cparams=ca.cparams(clevel=0))
    Array = open('example1', mode='w')
    c = Array.data.ca
    ctx = Context(env)

    for i in range(c.nchunks):
        chunk = c.chunks[i]
        # read only access
        #x = c.chunks[0][:]
        # write access
        x = view(chunk)

        size = x.strides[0]
        args = (x, size)
        execute(ctx, args, fname='main')

        # this does a _save() behind the scenes
        c.chunks[i] = chunk

    ctx.destroy()

    rts = Runtime(1,2,3)
    rts.join()

    print Array
Пример #2
0
def chunked_eval(blz_expr, chunk_size=32768):
    operands, code = blz_expr.gen_blir()
    total_size = _dimension(operands)
    temps = [_temp_for(i, chunk_size) for i in operands]
    temp_op = [
        i for i in zip(temps, operands) if isinstance(i[1], blaze.Array)
    ]
    offset = 0
    accum = 0.0
    _, env = blir.compile(code)
    ctx = blir.Context(env)
    while offset < total_size:
        curr_chunk_size = min(total_size - offset, chunk_size)
        slice_chunk = slice(0, curr_chunk_size)
        slice_src = slice(offset, offset + curr_chunk_size)
        for temp, op in temp_op:
            temp[slice_chunk] = op[slice_src]

        accum += blir.execute(ctx,
                              args=temps + [curr_chunk_size],
                              fname='main')
        offset = slice_src.stop

    ctx.destroy()
    return accum
Пример #3
0
def test_cgen2_add():
    with namesupply():

        krn = ElementwiseKernel(
            [
                (IN  , VectorArg((300,), 'array[int]')),
                (IN  , VectorArg((300,), 'array[int]')),
                (OUT , VectorArg((300,), 'array[int]')),
            ],
            '_out0[i0] = _in0[i0] + _in1[i0]',
        )

        krn.verify()
        ast, env = krn.compile()

        ctx = Context(env)

        a = np.array(xrange(300), dtype='int32')
        b = np.array(xrange(300), dtype='int32')
        c = np.empty_like(b)

        execute(ctx, args=(a,b,c), fname='kernel0', timing=False)
        assert np.allclose(c, a + b)
Пример #4
0
def chunked_eval(blz_expr, chunk_size=32768):
    operands, code = blz_expr.gen_blir()
    total_size = _dimension(operands)
    temps = [_temp_for(i, chunk_size) for i in operands]
    temp_op = [i for i in zip(temps, operands) if isinstance(i[1], blaze.Array)]
    offset = 0
    accum = 0.0
    _, env = blir.compile(code)
    ctx = blir.Context(env)
    while offset < total_size:
        curr_chunk_size = min(total_size - offset, chunk_size)
        slice_chunk = slice(0, curr_chunk_size)
        slice_src = slice(offset, offset + curr_chunk_size)
        for temp, op in temp_op:
            temp[slice_chunk] = op[slice_src]

        accum += blir.execute(ctx, args=temps + [curr_chunk_size], fname="main")
        offset = slice_src.stop

    ctx.destroy()
    return accum
Пример #5
0
    for i in range(n) {
        for j in range(n) {
            x[i,j] = i+j;
        }
    }
}
"""

N = 15
ast, env = compile(source)

arr = np.eye(N, dtype='int32')
args = (arr, N)

ctx = Context(env)
execute(ctx, args, timing=True)
ctx.destroy()

print arr

#------------------------------------------------------------------------
# Vector Dot Product
#------------------------------------------------------------------------

N = 50000
A = np.arange(N, dtype='double')
B = np.arange(N, dtype='double')

source = open('samples/blir/dot.bl')
ast, env = compile(source.read())
Пример #6
0
    for i in range(n) {
        for j in range(n) {
            x[i,j] = i+j;
        }
    }
}
"""

N = 15
ast, env = compile(source)

arr = np.eye(N, dtype='int32')
args = (arr, N)

ctx = Context(env)
execute(ctx, args, timing=True)
ctx.destroy()

print arr

#------------------------------------------------------------------------
# Vector Dot Product
#------------------------------------------------------------------------

N = 50000
A = np.arange(N, dtype='double')
B = np.arange(N, dtype='double')

source = open('samples/blir/dot.bl')
ast, env = compile(source.read())