In the past few years, ever-increasing amounts of image data have been generated by users globally, and these images are routinely stored in cold storage systems in compressed formats. This article investigates the use of approximate storage that leverages the use of cheaper, lower reliability memories that can have higher error rates. Since traditional JPEG-based schemes based on variable-length coding are extremely sensitive to error, the direct use of approximate storage results in severe quality degradation. We propose an error-resilient adaptive-length coding (ALC) scheme that divides all symbols into two classes, based on their frequency of occurrence, where each class has a fixed-length codeword. This provides a balance between the reliability of fixed-length coding schemes, which have a high storage overhead, and the storage-efficiency of Huffman coding schemes, which show high levels of error on low-reliability storage platforms. Further, we use data partitioning to determine which bits are stored in approximate or reliable storage to lower the overall cost of storage. We show that ALC can be used with general non-volatile storage, and can substantially reduce the total cost compared to traditional JPEG-based storage.

Communication overheads in distributed systems constitute a large fraction of the total execution time, and limit the scalability of applications running on these systems. We propose a DCT-based approximate communication scheme that takes advantage of the error resiliency of several widely-used applications, and improves communication efficiency by substantially reducing message lengths. Our scheme is implemented into the Message Passing Interface (MPI) library. When evaluated on several representative MPI applications on a real cluster system, it is seen that the fraction of total execution time devoted to communication reduces from 59% to 23%, even accounting for the computational overhead required for DCT encoding. For many communication-intensive applications, it is shown that our approximate communication scheme effectively speeds up the total execution time without much loss in quality of the result.