Growth and usage trends for several data-intensive applications indicate that their datasets and processing requirements are growing very quickly. Meeting these rapidly increasing storage and processing demands requires architectures that scale processing power with the storage capacity and throughput. Active Disks integrate significant processing power and memory into a disk drive and allow application-specific code to be downloaded and executed in the disk. Active Disks naturally scale the processing power of the system with increasing storage capacity, offer dramatic reduction in data traffic and improve the price/performance for large installations by off-loading computation to inexpensive embedded disk processors. To program Active Disks, I will describe a stream-based programming model that facilitates safety and efficiency of the disk-resident code (called disklets) while simplifying programming and restructuring of applications. I will also describe operating system support (called DiskOS) for the stream-based programming model to manage, coordinate and control disklet execution in conjunction with the host operating system. I will demonstrate the potential of Active Disks for a wide range of data-intensive applications from data-warehousing, data-mining, satellite data processing and digital microscopy. Results show that for the same I/O interconnect, disks and number of processors, Active Disks provide better price/performance than both

SMP-based conventional disk farms and commodity clusters. Active Disks outperform SMP-based disk farms by up to an order of magnitude in price as well as in performance and match (and in some cases improve upon) the performance of commodity clusters for less than half the price.