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Gauri Joshi – Carnegie Mellon University
March 27 @ 4:30 pm - 5:30 pm
Large-scale distribute computing frameworks such as MapReduce and Spark employ massive parallelization of jobs. While parallelism drastically reduces computation time, slow or straggling nodes can become a bottleneck in job completion. In this talk, we will study erasure codes for speeding up various types of distributed computation such as matrix-vector and matrix-matrix multiplications, convolutions and gradient descent.