TaP: table-based prefetching for storage caches
FAST'08 Proceedings of the 6th USENIX Conference on File and Storage Technologies
On the design of a new Linux readahead framework
ACM SIGOPS Operating Systems Review - Research and developments in the Linux kernel
Context-aware prefetching at the storage server
ATC'08 USENIX 2008 Annual Technical Conference on Annual Technical Conference
Dynamic partitioning of the cache hierarchy in shared data centers
Proceedings of the VLDB Endowment
Memory resource allocation for file system prefetching: from a supply chain management perspective
Proceedings of the 4th ACM European conference on Computer systems
InterferenceRemoval: removing interference of disk access for MPI programs through data replication
Proceedings of the 24th ACM International Conference on Supercomputing
Proceedings of the 3rd Annual Haifa Experimental Systems Conference
Management of Multilevel, Multiclient Cache Hierarchies with Application Hints
ACM Transactions on Computer Systems (TOCS)
A Prefetching Scheme Exploiting both Data Layout and Access History on Disk
ACM Transactions on Storage (TOS)
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State-of-the-art networked storage servers are equipped with increasingly powerful computing capability and large DRAMmemory as storage caches. However, their contribution to the performance improvement of networked storage system has become increasingly limited. This is because the client-side memory sizes are also increasing, which reduces capacity misses in the client buffer caches as well as access locality in the storage servers, thus weakening the caching effectiveness of server storage caches. Proactive caching in storage servers is highly desirable to reduce cold misses in clients. We propose an effective way to improve the utilization of storage server resources through prefetching in storage servers for clients. In particular, our design well utilizes two unique strengths of networked storage servers which are not leveraged in existing storage server prefetching schemes. First, powerful storage servers have idle CPU cycles, under-utilized disk bandwidth, and abundant memory space, providing many opportunities for aggressive disk data prefetching. Second, the servers have the knowledge about high-latency operations in storage devices, such as disk head positioning, which enables efficient disk data prefetching based on an accurate cost-benefit analysis of prefetch operations.We present STEP - a Sequentiality and Thrashing dEtection based Prefetching scheme, and its implementation with Linux Kernel 2.6.16. Our performance evaluation by replaying Storage Performance Council (SPC)'s OLTP traces shows that server performance improvements are up to 94% with an average of 25%. Improvements with frequently used Unix applications are up to 53% with an average of 12%. Our experiments also show that STEP has little effect on workloads with random access patterns, such as SPC' Web- Search traces.