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Modern operating systems (OSes) use a demand paging system to efficiently manage limited main memory shared by user applications. However, it does not perform well when launching an application in a “cold start” situation (i.e., none of its launch data blocks are hit in the OS page cache). In particular, it typically generates a non-sequential read accesses from hundreds of files on a hard disk drive (HDD), leading to poor disk throughput. Furthermore, a CPU is frequently blocked while waiting for disk I/O completion. This launch inefficiency can be largely mitigated by adopting solid state drives (SSDs), but there are still many systems that cannot afford the high cost per bit of SSDs, such as set-top boxes, video game consoles, and low-cost laptop or desktop PCs. Hence, optimization techniques that improve application launch performance on HDDs will remain useful until HDDs totally disappear from the market. Application prefetching is a representative technique to mitigate the launch inefficiency. Once an application accesses a set of data blocks in a particular order during a launch, it is highly likely to access almost the same set of data blocks in almost the same order in the next launches [1]–[3]. Such an I/O sequence is called an application launch sequence in recent work [2]. The deterministic launch behavior of applications allows application prefetchers to predict with high accuracy what data block will be requested next. I/O Reordering and I/O interleaving are the two key techniques behind the application prefetchers. Suppose an application launch sequence consists of 10

Application Prefetcher Design Using both I/O Reordering and I/O Interleaving