Reading input from primary storage (i.e. the ingest phase) and aggregating results (i.e. the merge phase) are important pre- and post-processing steps in large batch computations. Unfortunately, today's data sets are so large that the ingest and …
Predicting access times is a crucial part of predicting hard disk drive performance. Existing approaches use white-box modeling and require intimate knowledge of the internal layout of the drive, which can take months to extract. Automatically …
Real-time systems and applications are becoming increasingly complex and often comprise multiple communicating tasks. The management of the individual tasks is well-understood, but the interaction of communicating tasks with different timing …
MapReduce-tailored distributed filesystems---such as HDFS for Hadoop MapReduce---and parallel high-performance computing filesystems are tailored for considerably different workloads. The purpose of our work is to examine the performance of each …
Parallel file systems are gaining in popularity in high-end computing centers as well as commercial data centers. High-end computing systems are expected to scale exponentially and to pose new challenges to their storage scalability in terms of cost …
Real-time systems are growing in size and complexity and must often manage multiple competing tasks in environments where CPU is not the only limited shared resource. Memory, network, and other devices may also be shared and system-wide performance …