Core Failure Mitigation in Integer Sum-of-Product Computations on Cloud Computing Systems

The decreasing mean-time-to-failure estimates in cloud computing systems indicate that multimedia applications running on such environments should be able to mitigate an increasing number of core failures at runtime. We propose a new roll-forward failure-mitigation approach for integer sum-of-product computations, with emphasis on generic matrix multiplication (GEMM) and convolution/crosscorrelation (CONV) routines. Our approach is based on the production of redundant results within the numerical representation of the outputs via the use of numerical packing. This differs from all existing roll-forward solutions that require a separate set of checksum (or duplicate) results. Our proposal imposes 37.5% reduction in the maximum output bitwidth supported in comparison to integer sum-of-product realizations performed on 32-bit integer representations which is comparable to the bitwidth requirement of checksum-methods for multiple core failure mitigation. Experiments with state-of-the-art GEMM and CONV routines running on a c4.8xlarge compute-optimized instance of amazon web services elastic compute cloud (AWS EC2) demonstrate that the proposed approach is able to mitigate up to one quadcore failure while achieving processing throughput that is: 1) comparable to that of the conventional, failure-intolerant, integer GEMM and CONV routines, 2) substantially superior to that of the equivalent roll-forward failure-mitigation method based on checksum streams. Furthermore, when used within an image retrieval framework deployed over a cluster of AWS EC2 spot (i.e., low-cost albeit terminatable) instances, our proposal leads to: 1) 16%-23% cost reduction against the equivalent checksum-based method and 2) more than 70% cost reduction against conventional failure-intolerant processing on AWS EC2 on-demand (i.e., higher-cost albeit guaranteed) instances.