Towards zero latency photonic switching in shared memory networks

Photonic networks-on-chip based on silicon photonics have been proposed to reduce latency and power consumption in future chip multi-core processors (CMP). However, high performance CMPs use a shared memory model which generates large numbers of short messages, creating high arbitration latency overhead for photonic switching networks. In this paper we explore techniques which intelligently use information from the memory hierarchy to predict communication in order to setup photonic circuits with reduced or eliminated arbitration latency. Firstly, we present a switch scheduling algorithm which arbitrates on a per memory transaction basis and holds open photonic circuits to exploit temporal locality. We show that this can reduce the average arbitration latency overhead by 60% and eliminate arbitration latency altogether for a signi cant proportion of memory transactions. We then show how this technique can be applied to multiple-socket shared memory systems with low latency and energy consumption penalties. Finally, we present ideas and initial results to demonstrate that cache miss prediction could be used to set up photonic circuits for more complex memory transactions and main memory accesses

Owner Prediction for Accelerating Cache-to-Cache Transfer Misses in a cc-NUMA Architecture

Cache misses for which data must be obtained from a remote cache (cache-to-cache transfer misses) account for an important fraction of the total miss rate. Unfortunately, cc-NUMA designs put the access to the directory information into the critical path of 3-hop misses, which significantly penalizes them compared to SMP designs. This work studies the use of owner prediction as a means of providing cc-NUMA multiprocessors with a more efficient support for cache-to-cache transfer misses. Our proposal comprises an effective prediction scheme as well as a coherence protocol designed to support the use of prediction. Results indicate that owner prediction can significantly reduce the latency of cache-to-cache transfer misses, which translates into speed-ups on application performance up to 12%. In order to also accelerate most of those 3-hop misses that are either not predicted or mispredicted, the inclusion of a small and fast directory cache in every node is evaluated, leading to improvements up to 16% on the final performance

Owner Prediction for Accelerating Cache-to-Cache Transfer Misses in a cc-NUMA Architecture

Abstract Cache misses for which data must be obtained from a remote cache (cache-to

Predicting coherence communication by tracking synchronization points at run time.”

Abstract Predicting target processors that a coherence request must be delivered to can improve the miss handling latency in shared memory systems. In directory coherence protocols, directly communicating with the predicted processors avoids costly indirection to the directory. In snooping protocols, prediction relaxes the high bandwidth requirements by replacing broadcast with multicast. In this work, we propose a new run-time coherence target prediction scheme that exploits the inherent correlation between synchronization points in a program and coherence communication. Our workload-driven analysis shows that by exposing synchronization points to hardware and tracking them at run time, we can simply and effectively track stable and repetitive communication patterns. Based on this observation, we build a predictor that can improve the miss latency of a directory protocol by 13%. Compared with existing address-and instruction-based prediction techniques, our predictor achieves comparable performance using substantially smaller power and storage overheads

Synchronization-Point Driven Resource Management in Chip Multiprocessors.

With the proliferation of Chip Multiprocessors (CMPs), shared memory multi-threaded programs are expanding fast in every application domain. These programs exhibit execution characteristics that go beyond those observed in single-threaded programs, mainly due to data sharing and synchronization. To ensure that next generation CMPs will perform well on such anticipated workloads, it is vital to understand how these programs and architectures interact, and exploit the unique opportunities presented. This thesis examines the time-varying execution characteristics of the shared memory workloads in conjunction to the synchronization points that exist in the programs. The main hypothesis is that the type, the position, and the repetitive execution of synchronization constructs can be exploited to unfold important execution phases and enable new optimization opportunities. The research provides a simple application-driven approach for predicting the program behavior and effectively driving dynamic performance optimization and resource management actions in future CMPs. In the first part of this thesis, I show how synchronization points relate to various program-wide periodic behaviors. Based on the observations, I develop a framework where user-level synchronization primitives are exposed to the hardware and monitored to detect program phases and guide dynamic adaptation. Through workload-driven evaluation, I demonstrate the effectiveness of the framework in improving the performance/power in on-chip interconnects. The second part of the thesis explores in depth the inter-thread communication behaviors. I show that although synchronization points under the shared memory model do not expose any communication details, they indicate well the points where coherence communication patterns change or repeat. By leveraging this property, I design a synchronization-point-based coherence predictor that uncovers communication patterns with high accuracy, while consuming significantly less hardware resources compared to existing predictors. In the last part, I investigate the underlying reasons causing threads to wait in synchronization points, wasting resources. I show that these reasons can vary even across different programs phases, and existing critical-path predictors can render ineffective under certain conditions. I then present a new scheme that improves predictability by incorporating history information from previous points. The new design is robust and can amortize the run-time imbalances to improve the system's performance and/or energy

Efficient techniques to provide scalability for token-based cache coherence protocols

Cache coherence protocols based on tokens can provide low latency without relying on non-scalable interconnects thanks to the use of efficient requests that are unordered. However, when these unordered requests contend for the same memory block, they may cause protocols races. To resolve the races and ensure the completion of all the cache misses, token protocols use a starvation prevention mechanism that is inefficient and non-scalable in terms of required storage structures and generated traffic. Besides, token protocols use non-silent invalidations which increase the latency of write misses proportionally to the system size. All these problems make token protocols non-scalable. To overcome the main problems of token protocols and increase their scalability, we propose a new starvation prevention mechanism named Priority Requests. This mechanism resolves contention by an efficient, elegant, and flexible method based on ordered requests. Furthermore, thanks to Priority Requests, efficient techniques can be applied to limit the storage requirements of the starvation prevention mechanism, to reduce the total traffic generated for managing protocol races, and to reduce the latency of write misses. Thus, the main problems of token protocols can be solved, which, in turn, contributes to wide their efficiency and scalability.Cuesta Sáez, BA. (2009). Efficient techniques to provide scalability for token-based cache coherence protocols [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/6024Palanci

DeNovo: rethinking the memory hierarchy for disciplined parallelism

As multicore systems become widespread, both software and hardware face a major challenge in efficiently exploiting and implementing parallelism. While shared–memory remains a popular programming model due to its global address space, it is plagued with undisciplined programming practices that allow implicit communication and unstructured non-determinism. Such “wild” shared-memory behavior not only makes it difficult to test and maintain software but also complicates hardware, preventing it from scaling in a power-efficient manner. Recent research has proposed replacing the wild shared-memory programming models with a more disciplined approach. The DeNovo project asks the following question: if software is more disciplined, can we build more power-, performance-, and complexity-efficient shared-memory hardware? Focusing on deterministic programs as a discipline to drive DeNovo, we first show that coherence and communication can be made much simpler and more efficient than the current state of the art. The resulting protocol is without transient states, invalidation traffic, directory sharer–lists, or false sharing - all significant sources of inefficiencies in existing protocols. Widening the software space further, we then show how DeNovo can support software with disciplined non-determinism without giving up its benefits for deterministic programs. The remaining challenge is supporting synchronization accesses that are inherently “racy” on DeNovo without writer-initiated invalidation. We show that arbitrary synchronization can be supported on DeNovo with a simple yet efficient hardware mechanism, a big step toward our eventual goal of supporting legacy programs. Finally, we explore the potential for a comprehensive coherence solution that merges all previous DeNovo coherence mechanisms and adaptively switches between them depending on the level of “discipline” of software. In summary, DeNovo shows the potential for commercially viable software-driven shared-memory systems with higher complexity-, performance-, and energy-efficiency than today’s software-oblivious hardware