Memory resource allocation for file system prefetching: from a supply chain management perspective
Proceedings of the 4th ACM European conference on Computer systems
CLIC: client-informed caching for storage servers
FAST '09 Proccedings of the 7th conference on File and storage technologies
Dynamic storage cache allocation in multi-server architectures
Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis
Disk I/O based load balancing in VOD system
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
Adaptive multi-level cache allocation in distributed storage architectures
Proceedings of the 24th ACM International Conference on Supercomputing
Computation mapping for multi-level storage cache hierarchies
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Cashing in on hints for better prefetching and caching in PVFS and MPI-IO
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Management of Multilevel, Multiclient Cache Hierarchies with Application Hints
ACM Transactions on Computer Systems (TOCS)
Compiler-directed file layout optimization for hierarchical storage systems
SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Compiler-directed file layout optimization for hierarchical storage systems
Scientific Programming - Selected Papers from Super Computing 2012
| Hi-index | 0.00 |
In today's networked storage environment, it is common to have a hierarchy of caches where the lower levels of the hierarchy are accessed by multiple clients. This sharing can have both positive or negative effects. While data fetched by one client can be used by another client without incurring additional delays, clients competing for cache buffers can evict each other's blocks and interfere with exclusive caching schemes. Our algorithm, MC2, combines local, per client management with a global, system-wide, scheme, to emphasize the positive effects of sharing and reduce the negative ones. The local scheme uses readily available information about the client's future access profile to save the most valuable blocks, and to choose the best replacement policy for them. The global scheme uses the same information to divide the shared cache space between clients, and to manage this space. Exclusive caching is maintained for non-shared data and is disabled when sharing is identified. Our simulation results show that the combined algorithm significantly reduces the overall I/O response times of the system.