Dynamic memory dependence predication
Department of Computer Science; Center for Scalable Architectures and Systems
Store-queue-free architectures remove the store queue and use memory cloaking to communicate in-flight stores instead. In these architectures, frequent mispredictions may occur when the store to load dependencies are inconsistent. We present DMDP (Dynamic Memory Dependence Predication) which modifies the microarchitecture behavior for such loads to mitigate memory dependence mispredictions. When a given dependence is hard to predict, i.e., a given load occasionally depends on a particular store, but it is independent at other times, DMDP predicates the load so that the address of the load is compared with the address of the predicted store to compute a predicate. This predicate guides the load to obtain the value from either the cache or the colliding store. The predication provided by DMDP i) enables the loads and their dependent instructions to execute much earlier, ii) reduces the hardware complexity of store-queue-free mechanisms, and iii) reduces the number of mispredictions. DMDP outperforms a state-of-the-art store-queue-free architecture by 7.17% on Integer benchmarks and 4.48% on Float benchmarks in our Spec 2006 evaluation. We further show that despite executing extra predication instructions, DMDP is power efficient as it saves about 6.7% on EDP.
2018 ACM/IEEE 45th Annual International Symposium on Computer Architecture
Dynamic memory dependence predication.
2018 ACM/IEEE 45th Annual International Symposium on Computer Architecture.
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