Area-Efficient Near-Associative Memories on FPGAs

Abstract

Associative memories can map sparsely used keys to values with low latency but can incur heavy area overheads. The lack of customized hardware for associative memories in today’s mainstream FPGAs exacerbates the overhead cost of building these memories using the fixed address match BRAMs. In this article, we develop a new, FPGA-friendly, memory system architecture based on a multiple hash scheme that is able to achieve near-associative performance without the area-delay overheads of a fully associative memory on FPGAs. At the same time, we develop a novel memory management algorithm that allows us to statistically mimic an associative memory. Using the proposed architecture as a 64KB L1 data cache, we show that it is able to achieve near-associative miss rates while consuming 3--13 × fewer FPGA memory resources for a set of benchmark programs from the SPEC CPU2006 suite than fully associative memories generated by the Xilinx Coregen tool. Benefits for our architecture increase with key width, allowing area reduction up to 100 ×. Mapping delay is also reduced to 3.7ns for a 1,024-entry flat version or 6.1ns for an area-efficient version compared to 17.6ns for a fully associative memory for a 64-bit key on a Xilinx Virtex 6 device.