FreeLoader: Scavenging Desktop Storage Resources for Scientific Data Session: Storage and Data Event Type: Paper Time: 4:30pm - 5:00pm Session Chair: Erik Riedel Speaker(s): Sudharshan Vazhkudai, Xiaosong Ma, Vincent Freeh, Jonathan Strickland, Nandan Tammineedi, Stephen Scott Location: 602-604 Abstract: 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. This paper can be found in the ACM and IEEE Digital Libaries Click here for ACM Click here for IEEE Chair/Speaker Details: Erik Riedel (Chair) Seagate Research Sudharshan Vazhkudai Oak Ridge National Laboratory Xiaosong Ma North Carolina State University and Oak Ridge National Lab Vincent Freeh North Carolina State University Jonathan Strickland North Carolina State University Nandan Tammineedi North Carolina State University Stephen Scott Oak Ridge National Laboratory