Before revision:  We show that if the number of  workers is n, and the runtime of each subtask has an exponential tail, the optimal coded matrix multiplication is \Theta(\log n) times faster than the uncoded matrix multiplication. In data shuffling, we use codes to exploit the excess in storage and reduce communication bottlenecks .
After revision:  We show that if the number of workers is n, and the runtime of each subtask has an exponential tail, coded computation can speed up distributed matrix multiplication by a factor of \log n. For data shuffling, we use codes to exploit the excess in storage and reduce communication bottlenecks .