Brief announcement: Distributed shared memory based on computation migration

Driven by increasingly unbalanced technology scaling and power dissipation limits, microprocessor designers have resorted to increasing the number of cores on a single chip, and pundits expect 1000-core designs to materialize in the next few years [1]. But how will memory architectures scale and how will these next-generation multicores be programmed? One barrier to scaling current memory architectures is the offchip memory bandwidth wall [1,2]: off-chip bandwidth grows with package pin density, which scales much more slowly than on-die transistor density [3]. To reduce reliance on external memories and keep data on-chip, today’s multicores integrate very large shared last-level caches on chip [4]; interconnects used with such shared caches, however, do not scale beyond relatively few cores, and the power requirements and access latencies of large caches exclude their use in chips on a 1000-core scale. For massive-scale multicores, then, we are left with relatively small per-core caches. Per-core caches on a 1000-core scale, in turn, raise the question of memory coherence. On the one hand, a shared memory abstraction is a practical necessity for general-purpose programming, and most programmers prefer a shared memory model [5]. On the other hand, ensuring coherence among private caches is an expensive proposition: bus-based and snoopy protocols don’t scale beyond relatively few cores, and directory sizes needed in cache-coherence protocols must equal a significant portion of the combined size of the per-core caches as otherwise directory evictions will limit performance [6]. Moreover, directory-based coherence protocols are notoriously difficult to implement and verify [7]

DCC: A Dependable Cache Coherence Multicore Architecture

Cache coherence lies at the core of functionally-correct operation of shared memory multicores. Traditional directory-based hardware coherence protocols scale to large core counts, but they incorporate complex logic and directories to track coherence states. Technology scaling has reached miniaturization levels where manufacturing imperfections, device unreliability and occurrence of hard errors pose a serious dependability challenge. Broken or degraded functionality of the coherence protocol can lead to a non-operational processor or user visible performance loss. In this paper, we propose a dependable cache coherence architecture (DCC) that combines the traditional directory protocol with a novel execution-migration-based architecture to ensure dependability that is transparent to the programmer. Our architecturally redundant execution migration architecture only permits one copy of data to be cached anywhere in the processor: when a thread accesses an address not locally cached on the core it is executing on, it migrates to the appropriate core and continues execution there. Both coherence mechanisms can co-exist in the DCC architecture and we present architectural extensions to seamlessly transition between the directory and execution migration protocols

Self-aware Computing in the Angstrom Processor

Addressing the challenges of extreme scale computing requires holistic design of new programming models and systems that support those models. This paper discusses the Angstrom processor, which is designed to support a new Self-aware Computing (SEEC) model. In SEEC, applications explicitly state goals, while other systems components provide actions that the SEEC runtime system can use to meet those goals. Angstrom supports this model by exposing sensors and adaptations that traditionally would be managed independently by hardware. This exposure allows SEEC to coordinate hardware actions with actions specified by other parts of the system, and allows the SEEC runtime system to meet application goals while reducing costs (e.g., power consumption).United States. Defense Advanced Research Projects Agency. The Ubiquitous High Performance Computing Progra

ARCc: A case for an architecturally redundant cache-coherence architecture for large multicores

This paper proposes an architecturally redundant cache-coherence architecture (ARCc) that combines the directory and shared-NUCA based coherence protocols to improve performance, energy and dependability. Both coherence mechanisms co-exist in the hardware and ARCc enables seamless transition between the two protocols. We present an online analytical model implemented in the hardware that predicts performance and triggers a transition between the two coherence protocols at application-level granularity. The ARCc architecture delivers up to 1.6× higher performance and up to 1.5× lower energy consumption compared to the directory-based counterpart. It does so by identifying applications which benefit from the large shared cache capacity of shared-NUCA because of lower off-chip accesses, or where remote-cache word accesses are efficient.United States. Defense Advanced Research Projects Agency (DARPA UHPC Program

Interaction of NoC design and coherence protocol in 3D-Stacked CMPs

n/

Runtime-assisted cache coherence deactivation in task parallel programs

With increasing core counts, the scalability of directory-based cache coherence has become a challenging problem. To reduce the area and power needs of the directory, recent proposals reduce its size by classifying data as private or shared, and disable coherence for private data. However, existing classification methods suffer from inaccuracies and require complex hardware support with limited scalability. This paper proposes a hardware/software co-designed approach: the runtime system identifies data that is guaranteed by the programming model semantics to not require coherence and notifies the microarchitecture. The microarchitecture deactivates coherence for this private data and powers off unused directory capacity. Our proposal reduces directory accesses to just 26% of the baseline system, and supports a 64x smaller directory with only 2.8% performance degradation. By dynamically calibrating the directory size our proposal saves 86% of dynamic energy consumption in the directory without harming performance.This work has been supported by the RoMoL ERC Advanced Grant (GA 321253), by the European HiPEAC Network of Excellence, by the Spanish Ministry of Economy and Competitiveness (contract TIN2015-65316-P), by the Generalitat de Catalunya (contracts 2014-SGR-1051 and 2014-SGR-1272) and by the European Unions Horizon 2020 research and innovation programme (grant agreements 671697 and 779877). M. Moreto has been partially supported by the Spanish Ministry of Economy, Industry and Competitiveness under Ramon y Cajal fellowship number RYC-2016-21104.Peer ReviewedPostprint (author's final draft

Locality-oblivious cache organization leveraging single-cycle multi-hop NoCs

Locality has always been a critical factor in on-chip data placement on CMPs as accessing further-away caches has in the past been more costly than accessing nearby ones. Substantial research on locality-aware designs have thus focused on keeping a copy of the data private. However, this complicatesthe problem of data tracking and search/invalidation; tracking the state of a line at all on-chip caches at a directory or performing full-chip broadcasts are both non-scalable and extremely expensive solutions. In this paper, we make the case for Locality-Oblivious Cache Organization (LOCO), a CMP cache organization that leverages the on-chip network to create virtual single-cycle paths between distant caches, thus redefining the notion of locality. LOCO is a clustered cache organization, supporting both homogeneous and heterogeneous cluster sizes, and provides near single-cycle accesses to data anywhere within the cluster, just like a private cache. Globally, LOCO dynamically creates a virtual mesh connecting all the clusters, and performs an efficient global data search and migration over this virtual mesh, without having to resort to full-chip broadcasts or perform expensive directory lookups. Trace-driven and full system simulations running SPLASH-2 and PARSEC benchmarks show that LOCO improves application run time by up to 44.5% over baseline private and shared cache.Semiconductor Research CorporationUnited States. Defense Advanced Research Projects Agency (Semiconductor Technology Advanced Research Network

The case for a scalable coherence protocol for complex on-chip cache hierarchies in many-core systems

n/