Buddy-RAM: Improving the Performance and Efficiency of Bulk Bitwise Operations Using DRAM

Bitwise operations are an important component of modern day programming. Many widely-used data structures (e.g., bitmap indices in databases) rely on fast bitwise operations on large bit vectors to achieve high performance. Unfortunately, in existing systems, regardless of the underlying architecture (e.g., CPU, GPU, FPGA), the throughput of such bulk bitwise operations is limited by the available memory bandwidth. We propose Buddy, a new mechanism that exploits the analog operation of DRAM to perform bulk bitwise operations completely inside the DRAM chip, thereby not wasting any memory bandwidth. Buddy consists of two components. First, simultaneous activation of three DRAM rows that are connected to the same set of sense amplifiers enables us to perform bitwise AND and OR operations. Second, the inverters present in each sense amplifier enables us to perform bitwise NOT operations, with modest changes to the DRAM array. These two components, along with RowClone, a prior proposal for fast row copying inside DRAM, make Buddy functionally complete, thereby allowing it to perform any bitwise operation efficiently inside DRAM. Our implementation of Buddy largely exploits the existing DRAM structure and interface, and incurs low overhead (1% of DRAM chip area). Our evaluations based on SPICE simulations show that, across seven commonly-used bitwise operations, Buddy provides between 10.9X—25.6X improvement in raw throughput and 25.1X—59.5X reduction in energy consumption. We evaluate three real-world data-intensive applications that exploit bitwise operations. First, Buddy improves performance of database queries that use bitmap indices for fast analytics by 6.0X compared to a state-of-the-art baseline using SIMD operations. Second, Buddy accelerates BitWeaving, a recentlyproposed technique for fast database scans, by 7.0X on average across a wide range of scan parameters. Third, for the commonly-used set data structure, Buddy improves performance of set intersection, union, and difference operations by 3.0X compared to conventional implementations. We also describe four other promising applications that can benefit from Buddy, including DNA sequence analysis, encryption, and approximate statistics. We believe and hope that the large performance and energy improvements provided by Buddy can enable many other applications to use bitwise operations.