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Today's enterprise computing systems routinely employ a large number of computers for tasks ranging from supporting daily business operations to mission-critical back-end applications. These computers consume a lot of energy whose monetary cost accounts for a significant portion of an enterprise's operating budget. Consequently, enterprises employ energy saving techniques such as turning machines off overnight and dynamic energy management during the business hours. Unfortunately, dynamic energy management, especially that for disks, introduces delays when an accessed disk is in a low power state and needs to be brought into an active state. Existing techniques mainly focus on reducing energy consumption and do not take advantage of enterprise-wide resources to mitigate the associated delays. Thus, systems designers are faced with a critical trade-off: saving energy reduces operating costs but may increase the delays exposed to the users, conversely, reducing access latencies and making the system more responsive may preclude energy management techniques. In this paper, we propose System-wide Alternative Retrieval of Data (SARD) that exploits the large number of machines in an enterprise environment to transparently retrieve binaries from other nodes, thus avoiding access delays when the local disk is in a low power mode. SARD uses a software-based approach to reduce spin-up delays while eliminating the need for major operating system changes, custom buffering, or shared memory infrastructure. The main goal of SARD is not to increase energy savings, rather reduce delays associated with energy management techniques, which will encourage users to utilize energy management techniques more frequently and realize the energy savings. Our evaluation of SARD using trace-driven simulations as well as an actual implementation in a real system shows over 71% average reduction in delays associated with energy management. Moreover, SARD achieves an additional 5.1% average redu- - ction in energy consumption for typical desktop applications compared to the widely-used timeout-based disk energy management.