TY - GEN
T1 - FreeLoader
T2 - ACM/IEEE 2005 Supercomputing Conference, SC'05
AU - Vazhkudai, Sudharshan S.
AU - Ma, Xiaosong
AU - Frech, Vincent W.
AU - Strickland, Jonathan W.
AU - Tammineedi, Nandan
AU - Scott, Stephen L.
N1 - Publisher Copyright:
© 2005 IEEE.
PY - 2005
Y1 - 2005
N2 - High-end computing is suffering a data deluge from experiments, simulations, and apparatus that creates overwhelming application dataset sizes. End-user workstations - despite more processing power than ever before - are ill-equipped to cope with such data demands due to insufficient secondary storage space and I/O rates. Meanwhile, a large portion of desktop storage is unused. We present the FreeLoader framework, which aggregates unused desktop storage space and I/O bandwidth into a shared cache/scratch space, for hosting large, immutable datasets and exploiting data access locality. Our experiments show that FreeLoader is an appealing low-cost solution to storing massive datasets, by delivering higher data access rates than traditional storage facilities. In particular, we present novel data striping techniques that allow FreeLoader to efficiently aggregate a workstation's network communication bandwidth and local I/O bandwidth. In addition, the performance impact on the native workload of donor machines is small and can be effectively controlled.
AB - High-end computing is suffering a data deluge from experiments, simulations, and apparatus that creates overwhelming application dataset sizes. End-user workstations - despite more processing power than ever before - are ill-equipped to cope with such data demands due to insufficient secondary storage space and I/O rates. Meanwhile, a large portion of desktop storage is unused. We present the FreeLoader framework, which aggregates unused desktop storage space and I/O bandwidth into a shared cache/scratch space, for hosting large, immutable datasets and exploiting data access locality. Our experiments show that FreeLoader is an appealing low-cost solution to storing massive datasets, by delivering higher data access rates than traditional storage facilities. In particular, we present novel data striping techniques that allow FreeLoader to efficiently aggregate a workstation's network communication bandwidth and local I/O bandwidth. In addition, the performance impact on the native workload of donor machines is small and can be effectively controlled.
KW - Distributed storage
KW - Parallel I/O
KW - Scientific data management
KW - Serverless storage system
KW - Storage cache
KW - Storage scavenging
KW - Striped storage
UR - http://www.scopus.com/inward/record.url?scp=33845399711&partnerID=8YFLogxK
U2 - 10.1109/SC.2005.27
DO - 10.1109/SC.2005.27
M3 - Conference contribution
AN - SCOPUS:33845399711
SN - 1595930612
SN - 9781595930613
T3 - Proceedings of the ACM/IEEE 2005 Supercomputing Conference, SC'05
BT - Proceedings - Thirteenth International Symposium on Temporal Representation and Reasoning, TIME 2006
Y2 - 12 November 2005 through 18 November 2005
ER -