High-density data storage using proximal probe techniques
IBM Journal of Research and Development - Special issue on proximal probe microscopes
An analytic behavior model for disk drives with readahead caches and request reordering
SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Computer architecture (2nd ed.): a quantitative approach
Computer architecture (2nd ed.): a quantitative approach
Modeling and performance of MEMS-based storage devices
Proceedings of the 2000 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Designing computer systems with MEMS-based storage
ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
Workload based optimization of probe-based storage
SIGMETRICS '02 Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Selected Papers on Holographic Storage
Selected Papers on Holographic Storage
Physical Modeling of Probe-Based Storage
MSS '01 Proceedings of the Eighteenth IEEE Symposium on Mass Storage Systems and Technologies
Power Conservation Strategies for MEMS-Based Storage Devices
MASCOTS '02 Proceedings of the 10th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems
Awarded Best Paper! - Using MEMS-Based Storage in Disk Arrays
FAST '03 Proceedings of the 2nd USENIX Conference on File and Storage Technologies
Operating system management of MEMS-based storage devices
OSDI'00 Proceedings of the 4th conference on Symposium on Operating System Design & Implementation - Volume 4
Computer
The "Millipede": more than one thousand tips for future AFM data storage
IBM Journal of Research and Development
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Probe-based storage, also known as micro-electric mechanical systems (MEMS) storage, is a new technology that is emerging to bypass the fundamental limitations of disk drives. The design space of such devices is particularly interesting because we can architect these devices to different design points, each with different performance characteristics. This makes it more difficult to understand how to use probe-based storage in a system. Although researchers have modeled access times and simulated performance of workloads, such simulations are time-intensive and make it difficult to exhaustively search the parameter space for optimal configurations. To address this problem, we have created a parameterized analytical model that computes the average request latency of a probe-based storage device. Our error compared to a simulated device using real-world traces is small (less than 15% for service time). With this model we can identify configurations that will satisfy specific performance objectives, greatly narrowing the search space of configurations one must simulate.