Abstract
Modern DRAM devices for the main memory are structured to have multiple banks to satisfy ever-increasing throughput, energy-efficiency, and capacity demands. Due to tight cost constraints, only one row can be buffered (opened) per bank and actively service requests at a time, while the row must be deactivated (closed) before a new row is stored into the row buffers. Hasty deactivation unnecessarily re-opens rows for otherwise row-buffer hits while hindsight accompanies the deactivation process on the critical path of accessing data for row-buffer misses. The time to (de)activate a row is comparable to the time to read an open row while applications are often sensitive to DRAM latency. Hence, it is critical to make the right decision on when to close a row. However, the increasing number of banks per DRAM device over generations reduces the number of requests per bank. This forces a memory controller to frequently predict when to close a row due to a lack of information on future requests, while the dynamic nature of memory access patterns limits the prediction accuracy In this paper, we propose a novel DRAM microarchitecture that can eliminate the need for any prediction. First, we identify that precharging the bitlines dominates the deactivate time, while sense amplifiers that work as a row buffer are physically coupled with the bitlines such that a single command precharges both bitlines and sense amplifiers simultaneously. By decoupling the bitlines from the row buffers using isolation transistors, the bitlines can be precharged right after a row becomes activated. Therefore, only the sense amplifiers need to be precharged for a miss in most cases, taking an order of magnitude shorter time than the conventional deactivation process. Second, we show that this row-buffer decoupling enables internal DRAM ?-operations to be separated and recombined, which can be exploited by memory controllers to make the main memory system more energy efficient. Our experiments demonstrate that row-buffer decoupling improves the geometric mean of the instructions per cycle and MIPS2/W by 14% and 29%, respectively, for memory-intensive SPEC CPU2006 applications
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