Switch-based packing technique to reduce traffic and latency in token coherence

Token Coherence is a cache coherence protocol able to simultaneously capture the best attributes of traditional protocols: low latency and scalability. However it may lose these desired features when (1) several nodes contend for the same memory block and (2) nodes write highly-shared blocks. The first situation leads to the issue of simultaneous broadcast requests which threaten the protocol scalability. The second situation results in a burst of token responses directed to the writer, which turn it into a bottleneck and increase the latency. To address these problems, we propose a switch-based packing technique able to encapsulate several messages (while in transit) into just one. Its application to the simultaneous broadcasts significantly reduces their bandwidth requirements (up to 45%). Its application to token responses lowers their transmission latency (by 70%). Thus, the packing technique decreases both the latency and coherence traffic, thereby improving system performance (about 15% of reduction in runtime). © 2011 Elsevier Inc. All rights reserved.This work was partially supported by the Spanish MEC and MICINN, as well as European Commission FEDER funds, under Grants CSD2006-00046 and TIN2009-14475-C04-01.Cuesta Sáez, BA.; Robles Martínez, A.; Duato Marín, JF. (2012). Switch-based packing technique to reduce traffic and latency in token coherence. Journal of Parallel and Distributed Computing. 72(3):409-423. https://doi.org/10.1016/j.jpdc.2011.11.010S40942372

Design and implementation of in-network coherence

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.Title as it appears in MIT Commencement Exercises program, June 2013: Design and implementation of in-network coherence. Cataloged from PDF version of thesis.Includes bibliographical references (p. 101-104).CMOS technology scaling has enabled increasing transistor density on chip. At the same time, multi-core processors that provide increased performance, vis-a'-vis power efficiency, have become prevalent in a power constrained environment. The shared memory model is a predominant paradigm in such systems, easing programmability and increasing portability. However with memory being shared by an increasing number of cores, a scalable coherence mechanism is imperative for these systems. Snoopy coherence has been a favored coherence scheme owing to its high performance and simplicity. However there are few viable proposals to extend snoopy coherence to unordered interconnects - specifically, modular packet-switched interconnects that have emerged as a scalable solution to the communication challenges in the CMP era. This thesis proposes a distributed in-network global ordering scheme that enables snoopy coherence on unordered interconnects. The proposed scheme is realized on a two-dimensional mesh interconnection network, referred to as OMNI (Ordered Mesh Network Interconnect). OMNI is an enabling solution for the SCORPIO processor prototype developed at MIT - a 36-core chip multi-processor supporting snoopy coherence, and fabricated in a commercial 45nm technology. OMNI is shown to be effective, reducing runtime by 36% in comparison to directory and Hammer coherence protocol implementations. The OMNI network achieves an operating frequency of 833 MHz post-layout, occupies 10% of the chip area, and consumes less than 100mW of power.by Suvinay Subramanian.S.M

Timing Predictable and High-Performance Hardware Cache Coherence Mechanisms for Real-Time Multi-Core Platforms

Multi-core platforms are becoming primary compute platforms for real-time systems such as avionics and autonomous vehicles. This adoption is primarily driven by the increasing application demands deployed in real-time systems, and the cost and performance benefits of multi-core platforms. For real-time applications, satisfying safety properties in the form of timing predictability, is the paramount consideration. Providing such guarantees on safety properties requires applying some timing analysis on the application executing on the compute platform. The timing analysis computes an upper bound on the application’s execution time on the compute platform, which is referred to as the worst-case execution time (WCET). However, multi-core platforms pose challenges that complicate the timing analysis. Among these challenges are timing challenges caused due to simultaneous accesses from multiple cores to shared hardware resources such as shared caches, interconnects, and off-chip memories. Supporting timing predictable shared data communication between real-time applications further compounds this challenge as a core’s access to shared data is dependent on the simultaneous memory activity from other cores on the shared data. Although hardware cache coherence mechanisms are the primary high-performance data communication mechanisms in current multi-core platforms, there has been very little use of these mechanisms to support timing predictable shared data communication in real-time multi-core platforms. Rather, current state-of-the-art approaches to timing predictable shared data communication sidestep hardware cache coherence. These approaches enforce memory and execution constraints on the shared data to simplify the timing analysis at the expense of application performance. This thesis makes the case for timing predictable hardware cache coherence mechanisms as viable shared data communication mechanisms for real-time multi-core platforms. A key takeaway from the contributions in this thesis is that timing predictable hardware cache coherence mechanisms offer significant application performance over prior state-of-the-art data communication approaches while guaranteeing timing predictability. This thesis has three main contributions. First, this thesis shows how a hardware cache coherence mechanism can be designed to be timing predictable by defining design invariants that guarantee timing predictability. We apply these design invariants and design timing predictable variants of existing conventional cache coherence mechanisms. Evaluation of these timing predictable cache coherence mechanisms show that they provide significant application performance over state-of-the-art approaches while delivering timing predictability. Second, we observe that the large worst-case memory access latency under timing predictable hardware cache coherence mechanisms questions their applicability as a data communication mechanism in real-time multi-core platforms. To this end, we present a systematic framework to design better timing predictable cache coherence mechanisms that balance high application performance and low worst-case memory access latency. Our systematic framework concisely captures the design features of timing predictable cache coherence mechanisms that impacts their WCET, and identifies a spectrum of approaches to reduce the worst-case memory access latency. We describe one approach and show that this approach reduces the worst-case memory access latency of timing predictable cache coherence mechanisms to be the same as alternative approaches while trading away minimal performance in the original cache coherence mechanisms. Third, we design a timing predictable hardware cache coherence mechanism for multi-core platforms used in mixed-critical real-time systems (MCS). Applications in MCS have varying performance and timing predictability requirements. We design a timing predictable cache coherence mechanism that considers these differing requirements and ensures that applications with no timing predictability requirements do not impact applications with strict predictability requirements