Dual Vector Load for Improved Pipelining in Vector Processors
Viktor Razilov, Juncen Zhong, Emil Matúš, Gerhard Paul Fettweis · 2023
Vector processors execute instructions that manipulate vectors of data items using time-division multiplexing (TDM). Chaining, the pipelined execution of vector instruction, ensures high performance and utilization. When two vectors are loaded sequentially to be the input of a follow-up compute instruction, which is often the case in vector applications, chaining cannot take effect during the duration of the entire first vector load. To close this gap, we propose dual load: A parallel or interleaved load of the two input vectors. We study this feature analytically and make statements on necessary conditions for performance improvements. Our investigation finds that compute-bound and some memory-bound applications profit from this feature when the memory and compute bandwidths are sufficiently high. A speedup of up to 33 % is possible in the ideal case. Our practical implementation shows improvements of up to 21 % with a hardware overhead of less than 2 %.