FADE: A programmable filtering accelerator for instruction-grain monitoring

Sotiria Fytraki, Evangelos Vlachos, Onur Kocberber, Babak Falsafi, Boris Grot
2014 2014 IEEE 20th International Symposium on High Performance Computer Architecture (HPCA)  
Instruction-grain monitoring is a powerful approach that enables a wide spectrum of bug-finding tools. As existing software approaches incur prohibitive runtime overhead, researchers have focused on hardware support for instruction-grain monitoring. A recurring theme in recent work is the use of hardware-assisted filtering so as to elide costly software analysis. This work generalizes and extends prior point solutions into a programmable filtering accelerator affording vast flexibility and
more » ... eed event filtering. The pipelined microarchitecture of the accelerator affords a peak filtering rate of one application event per cycle, which suffices to keep up with an aggressive OoO core running the monitored application. A unique feature of the proposed design is the ability to dynamically resolve dependencies between unfilterable events and subsequent events, eliminating data-dependent stalls and maximizing accelerator's performance. Our evaluation results show a monitoring slowdown of just 1.2-1.8x across a diverse set of monitoring tools.
doi:10.1109/hpca.2014.6835922 dblp:conf/hpca/FytrakiVKFG14 fatcat:nc4v4tuuefftvo3ji4miiuymeu