Louvre: Lightweight Ordering Using Versioning for Release Consistency

TL;DR

Louvre introduces a lightweight versioning mechanism for fences in weakly consistent multi-core processors, reducing overhead and improving performance by relaxing ordering constraints and minimizing stalls.

Contribution

The paper proposes a novel versioning-based approach to relax fence constraints, decreasing execution overhead and enhancing performance in weakly consistent memory models.

Findings

Reduces ordering instruction latency by 39.6%.

Improves overall program performance by 11%.

Effectively relaxes fence constraints to optimize execution.

Abstract

Fence instructions are fundamental primitives that ensure consistency in a weakly consistent shared memory multi-core processor. The execution cost of these instructions is significant and adds a non-trivial overhead to parallel programs. In a naive architecture implementation, we track the ordering constraints imposed by a fence by its entry in the reorder buffer and its execution overhead entails stalling the processor's pipeline until the store buffer is drained and also conservatively invalidating speculative loads. These actions create a cascading effect of increased overhead on the execution of the following instructions in the program. We find these actions to be overly restrictive and that they can be further relaxed thereby allowing aggressive optimizations. The current work proposes a lightweight mechanism in which we assign ordering tags, called versions, to load and store instructions when they reside in the load/store queues and the write buffer. The version assigned to a memory access allows us to fully exploit the relaxation allowed by the weak consistency model and restricts its execution in such a way that the ordering constraints by the model are satisfied. We utilize the information captured through the assigned versions to reduce stalls caused by waiting for the store buffer to drain and to avoid unnecessary squashing of speculative loads, thereby minimizing the re-execution penalty. This method is particularly effective for the release consistency model that employs uni-directional fence instructions. We show that this mechanism reduces the ordering instruction latency by 39.6% and improves program performance by 11% on average over the baseline implementation.