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@cuda.jit(device=True)
def compute_skew_with_mean(array,skew,mean):
    # skew is a shared memory array
    # mean is a scaler, the mean value of array
    # len(skew) == TPB+1
    # TPB: constant, threads per block, 32 in this case
    # the kernel has only one thread block, so no global sync required.
    # the final result is in skew[0]
    tid = cuda.threadIdx.x
    initialize(skew,0,len(skew))

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got = df.groupby('object_id').apply_grouped(compute_skew,
                              incols=['flux'],
                              outcols={'skew_flux': np.float64}
                              tpb=32)