High-performance reconfigurable computing involves acceleration of significant portions of an application using reconfigurable hardware. When the hardware tasks of an application cannot simultaneously fit in an FPGA, the task graph needs to be partitioned and scheduled into multiple FPGA configurations, in a way that minimizes the total execution time. This article proposes the Reduced Data Movement Scheduling (RDMS) algorithm that aims to improve the overall performance of hardware tasks by taking into account the reconfiguration time, data dependency between tasks, intertask communication as well as task resource utilization. The proposed algorithm uses the dynamic programming method. A mathematical analysis of the algorithm shows that the execution time would at most exceed the optimal solution by a factor of around 1.6, in the worst-case. Simulations on randomly generated task graphs indicate that RDMS algorithm can reduce interconfiguration communication time by 11% and 44% respectively, compared with two other approaches that consider data dependency and hardware resource utilization only. The practicality, as well as efficiency of the proposed algorithm over other approaches, is demonstrated by simulating a task graph from a real-life application -N-body simulation -along with constraints for bandwidth and FPGA parameters from existing high-performance reconfigurable computers. Experiments on SRC-6 are carried out to validate the approach.
Solid-State Drives (SSDs) are data storage devices that use solid-state memory to store persistent data. Flash memory is the de facto nonvolatile technology used in most SSDs. It is well known that the writing performance of flash-based SSDs is much lower than the reading performance due to the fact that a flash page can be written only after it is erased. In this work, we present an SSD cache architecture designed to provide a balanced read/write performance for flash memory. An efficient automatic updating technique is proposed to provide a more responsive SSD architecture by writing back stable but dirty flash pages according to a predetermined set of policies during the SSD device idle time. Those automatic updating policies are also tested and compared. Simulation results demonstrate that both reading and writing performance are improved significantly by incorporating the proposed cache with automatic updating feature into SSDs.
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