A Study on Performance and Power Efficiency of Dense Non-Volatile Caches in Multi-Core Systems

In this paper, we present a novel cache design based on Multi-Level Cell Spin-Transfer Torque RAM (MLC STTRAM) that can dynamically adapt the set capacity and associativity to use efficiently the full potential of MLC STTRAM. We exploit the asymmetric nature of the MLC storage scheme to build cache lines featuring heterogeneous performances, that is, half of the cache lines are read-friendly, while the other is write-friendly. Furthermore, we propose to opportunistically deactivate ways in underutilized sets to convert MLC to Single-Level Cell (SLC) mode, which features overall better performance and lifetime. Our ultimate goal is to build a cache architecture that combines the capacity advantages of MLC and performance/energy advantages of SLC. Our experiments show an improvement of 43% in total numbers of conflict misses, 27% in memory access latency, 12% in system performance, and 26% in LLC access energy, with a slight degradation in cache lifetime (about 7%) compared to an SLC cache

Novel Cache Hierarchies with Photonic Interconnects for Chip Multiprocessors

[ES] Los procesadores multinúcleo actuales cuentan con recursos compartidos entre los diferentes núcleos. Dos de estos recursos compartidos, la cache de último nivel y el ancho de banda de memoria principal, pueden convertirse en cuellos de botella para el rendimiento. Además, con el crecimiento del número de núcleos que implementan los diseños más recientes, la red dentro del chip también se convierte en un cuello de botella que puede afectar negativamente al rendimiento, ya que las redes tradicionales pueden encontrar limitaciones a su escalabilidad en el futuro cercano. Prácticamente la totalidad de los diseños actuales implementan jerarquías de memoria que se comunican mediante rápidas redes de interconexión. Esta organización es eficaz dado que permite reducir el número de accesos que se realizan a memoria principal y la latencia media de acceso a memoria. Las caches, la red de interconexión y la memoria principal, conjuntamente con otras técnicas conocidas como la prebúsqueda, permiten reducir las enormes latencias de acceso a memoria principal, limitando así el impacto negativo ocasionado por la diferencia de rendimiento existente entre los núcleos de cómputo y la memoria. Sin embargo, compartir los recursos mencionados es fuente de diferentes problemas y retos, siendo uno de los principales el manejo de la interferencia entre aplicaciones. Hacer un uso eficiente de la jerarquía de memoria y las caches, así como contar con una red de interconexión apropiada, es necesario para sostener el crecimiento del rendimiento en los diseños tanto actuales como futuros. Esta tesis analiza y estudia los principales problemas e inconvenientes observados en estos dos recursos: la cache de último nivel y la red dentro del chip. En primer lugar, se estudia la escalabilidad de las tradicionales redes dentro del chip con topología de malla, así como esta puede verse comprometida en próximos diseños que cuenten con mayor número de núcleos. Los resultados de este estudio muestran que, a mayor número de núcleos, el impacto negativo de la distancia entre núcleos en la latencia puede afectar seriamente al rendimiento del procesador. Como solución a este problema, en esta tesis proponemos una de red de interconexión óptica modelada en un entorno de simulación detallado, que supone una solución viable a los problemas de escalabilidad observados en los diseños tradicionales. A continuación, esta tesis dedica un esfuerzo importante a identificar y proponer soluciones a los principales problemas de diseño de las jerarquías de memoria actuales como son, por ejemplo, el sobredimensionado del espacio de cache privado, la existencia de réplicas de datos y rigidez e incapacidad de adaptación de las estructuras de cache. Aunque bien conocidos, estos problemas y sus efectos adversos en el rendimiento pueden ser evitados en procesadores de alto rendimiento gracias a la enorme capacidad de la cache de último nivel que este tipo de procesadores típicamente implementan. Sin embargo, en procesadores de bajo consumo, no existe la posibilidad de contar con tales capacidades y hacer un uso eficiente del espacio disponible es crítico para mantener el rendimiento. Como solución a estos problemas en procesadores de bajo consumo, proponemos una novedosa organización de jerarquía de dos niveles cache que utiliza una red de interconexión óptica. Los resultados obtenidos muestran que, comparado con diseños convencionales, el consumo de energía estática en la arquitectura propuesta es un 60% menor, pese a que los resultados de rendimiento presentan valores similares. Por último, hemos extendido la arquitectura propuesta para dar soporte tanto a aplicaciones paralelas como secuenciales. Los resultados obtenidos con la esta nueva arquitectura muestran un ahorro de hasta el 78 % de energía estática en la ejecución de aplicaciones paralelas.[CA] Els processadors multinucli actuals compten amb recursos compartits entre els diferents nuclis. Dos d'aquests recursos compartits, la memòria d’últim nivell i l'ample de banda de memòria principal, poden convertir-se en colls d'ampolla per al rendiment. A mes, amb el creixement del nombre de nuclis que implementen els dissenys mes recents, la xarxa dins del xip també es converteix en un coll d'ampolla que pot afectar negativament el rendiment, ja que les xarxes tradicionals poden trobar limitacions a la seva escalabilitat en el futur proper. Pràcticament la totalitat dels dissenys actuals implementen jerarquies de memòria que es comuniquen mitjançant rapides xarxes d’interconnexió. Aquesta organització es eficaç ates que permet reduir el nombre d'accessos que es realitzen a memòria principal i la latència mitjana d’accés a memòria. Les caches, la xarxa d’interconnexió i la memòria principal, conjuntament amb altres tècniques conegudes com la prebúsqueda, permeten reduir les enormes latències d’accés a memòria principal, limitant així l'impacte negatiu ocasionat per la diferencia de rendiment existent entre els nuclis de còmput i la memòria. No obstant això, compartir els recursos esmentats és font de diversos problemes i reptes, sent un dels principals la gestió de la interferència entre aplicacions. Fer un us eficient de la jerarquia de memòria i les caches, així com comptar amb una xarxa d’interconnexió apropiada, es necessari per sostenir el creixement del rendiment en els dissenys tant actuals com futurs. Aquesta tesi analitza i estudia els principals problemes i inconvenients observats en aquests dos recursos: la memòria cache d’últim nivell i la xarxa dins del xip. En primer lloc, s'estudia l'escalabilitat de les xarxes tradicionals dins del xip amb topologia de malla, així com aquesta es pot veure compromesa en propers dissenys que compten amb major nombre de nuclis. Els resultats d'aquest estudi mostren que, a major nombre de nuclis, l'impacte negatiu de la distància entre nuclis en la latència pot afectar seriosament al rendiment del processador. Com a solució' a aquest problema, en aquesta tesi proposem una xarxa d’interconnexió' òptica modelada en un entorn de simulació detallat, que suposa una solució viable als problemes d'escalabilitat observats en els dissenys tradicionals. A continuació, aquesta tesi dedica un esforç important a identificar i proposar solucions als principals problemes de disseny de les jerarquies de memòria actuals com son, per exemple, el sobredimensionat de l'espai de memòria cache privat, l’existència de repliques de dades i la rigidesa i incapacitat d’adaptació' de les estructures de memòria cache. Encara que ben coneguts, aquests problemes i els seus efectes adversos en el rendiment poden ser evitats en processadors d'alt rendiment gracies a l'enorme capacitat de la memòria cache d’últim nivell que aquest tipus de processadors típicament implementen. No obstant això, en processadors de baix consum, no hi ha la possibilitat de comptar amb aquestes capacitats, i fer un us eficient de l'espai disponible es torna crític per mantenir el rendiment. Com a solució a aquests problemes en processadors de baix consum, proposem una nova organització de jerarquia de dos nivells de memòria cache que utilitza una xarxa d’interconnexió òptica. Els resultats obtinguts mostren que, comparat amb dissenys convencionals, el consum d'energia estàtica en l'arquitectura proposada és un 60% menor, malgrat que els resultats de rendiment presenten valors similars. Per últim, hem estes l'arquitectura proposada per donar suport tant a aplicacions paral·leles com seqüencials. Els resultats obtinguts amb aquesta nova arquitectura mostren un estalvi de fins al 78 % d'energia estàtica en l’execució d'aplicacions paral·leles.[EN] Current multicores face the challenge of sharing resources among the different processor cores. Two main shared resources act as major performance bottlenecks in current designs: the off-chip main memory bandwidth and the last level cache. Additionally, as the core count grows, the network on-chip is also becoming a potential performance bottleneck, since traditional designs may find scalability issues in the near future. Memory hierarchies communicated through fast interconnects are implemented in almost every current design as they reduce the number of off-chip accesses and the overall latency, respectively. Main memory, caches, and interconnection resources, together with other widely-used techniques like prefetching, help alleviate the huge memory access latencies and limit the impact of the core-memory speed gap. However, sharing these resources brings several concerns, being one of the most challenging the management of the inter-application interference. Since almost every running application needs to access to main memory, all of them are exposed to interference from other co-runners in their way to the memory controller. For this reason, making an efficient use of the available cache space, together with achieving fast and scalable interconnects, is critical to sustain the performance in current and future designs. This dissertation analyzes and addresses the most important shortcomings of two major shared resources: the Last Level Cache (LLC) and the Network on Chip (NoC). First, we study the scalability of both electrical and optical NoCs for future multicoresand many-cores. To perform this study, we model optical interconnects in a cycle-accurate multicore simulation framework. A proper model is required; otherwise, important performance deviations may be observed otherwise in the evaluation results. The study reveals that, as the core count grows, the effect of distance on the end-to-end latency can negatively impact on the processor performance. In contrast, the study also shows that silicon nanophotonics are a viable solution to solve the mentioned latency problems. This dissertation is also motivated by important design concerns related to current memory hierarchies, like the oversizing of private cache space, data replication overheads, and lack of flexibility regarding sharing of cache structures. These issues, which can be overcome in high performance processors by virtue of huge LLCs, can compromise performance in low power processors. To address these issues we propose a more efficient cache hierarchy organization that leverages optical interconnects. The proposed architecture is conceived as an optically interconnected two-level cache hierarchy composed of multiple cache modules that can be dynamically turned on and off independently. Experimental results show that, compared to conventional designs, static energy consumption is improved by up to 60% while achieving similar performance results. Finally, we extend the proposal to support both sequential and parallel applications. This extension is required since the proposal adapts to the dynamic cache space needs of the running applications, and multithreaded applications's behaviors widely differ from those of single threaded programs. In addition, coherence management is also addressed, which is challenging since each cache module can be assigned to any core at a given time in the proposed approach. For parallel applications, the evaluation shows that the proposal achieves up to 78% static energy savings. In summary, this thesis tackles major challenges originated by the sharing of on-chip caches and communication resources in current multicores, and proposes new cache hierarchy organizations leveraging optical interconnects to address them. The proposed organizations reduce both static and dynamic energy consumption compared to conventional approaches while achieving similar performance; which results in better energy efficiency.Puche Lara, J. (2021). Novel Cache Hierarchies with Photonic Interconnects for Chip Multiprocessors [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/165254TESI

ANALYTICAL MODEL FOR CHIP MULTIPROCESSOR MEMORY HIERARCHY DESIGN AND MAMAGEMENT

Continued advances in circuit integration technology has ushered in the era of chip multiprocessor (CMP) architectures as further scaling of the performance of conventional wide-issue superscalar processor architectures remains hard and costly. CMP architectures take advantageof Moore¡¯s Law by integrating more cores in a given chip area rather than a single fastyet larger core. They achieve higher performance with multithreaded workloads. However,CMP architectures pose many new memory hierarchy design and management problems thatmust be addressed. For example, how many cores and how much cache capacity must weintegrate in a single chip to obtain the best throughput possible? Which is more effective,allocating more cache capacity or memory bandwidth to a program?This thesis research develops simple yet powerful analytical models to study two newmemory hierarchy design and resource management problems for CMPs. First, we considerthe chip area allocation problem to maximize the chip throughput. Our model focuses onthe trade-off between the number of cores, cache capacity, and cache management strategies.We find that different cache management schemes demand different area allocation to coresand cache to achieve their maximum performance. Second, we analyze the effect of cachecapacity partitioning on the bandwidth requirement of a given program. Furthermore, ourmodel considers how bandwidth allocation to different co-scheduled programs will affect theindividual programs¡¯ performance. Since the CMP design space is large and simulating only one design point of the designspace under various workloads would be extremely time-consuming, the conventionalsimulation-based research approach quickly becomes ineffective. We anticipate that ouranalytical models will provide practical tools to CMP designers and correctly guide theirdesign efforts at an early design stage. Furthermore, our models will allow them to betterunderstand potentially complex interactions among key design parameters

Reactive NUCA: Near-Optimal Block Placement and Replication in Distributed Caches

Increases in on-chip communication delay and the large working sets of server and scientific workloads complicate the design of the on-chip last- level cache for multicore processors. The large working sets favor a shared cache design that maximizes the aggregate cache capacity and minimizes off-chip memory requests. At the same time, the growing on-chip communication delay favors core-private caches that replicate data to minimize delays on global wires. Recent hybrid proposals offer lower average latency than conventional designs, but they address the placement requirements of only a subset of the data accessed by the application, require complex lookup and coherence mechanisms that increase latency, or fail to scale to high core counts. In this work, we observe that the cache access patterns of a range of server and scientific workloads can be classified into distinct classes, where each class is amenable to different block placement policies. Based on this observation, we propose Reactive NUCA (R- NUCA), a distributed cache design which reacts to the class of each cache access and places blocks at the appropriate location in the cache. R-NUCA cooperates with the operating system to support intelligent placement, migration, and replication without the overhead of an explicit coherence mechanism for the on-chip last-level cache. In a range of server, scientific, and multi-programmed workloads, R-NUCA matches the performance of the best cache design for each workload, improving performance by 14% on average over competing designs and by 32% at best, while achieving performance within 5% of an ideal cache design

Implementing a hybrid SRAM / eDRAM NUCA architecture

In this paper, we propose a hybrid cache architecture that exploits the main features of both memory technologies, speed of SRAM and high density of eDRAM. We demonstrate, that due to the high locality found in emerging applications, a high percentage of data that enters to the on-chip last-level cache are not accessed again before they are replacedPreprin

Doctor of Philosophy

dissertationIn recent years, a number of trends have started to emerge, both in microprocessor and application characteristics. As per Moore's law, the number of cores on chip will keep doubling every 18-24 months. International Technology Roadmap for Semiconductors (ITRS) reports that wires will continue to scale poorly, exacerbating the cost of on-chip communication. Cores will have to navigate an on-chip network to access data that may be scattered across many cache banks. The number of pins on the package, and hence available off-chip bandwidth, will at best increase at sublinear rate and at worst, stagnate. A number of disruptive memory technologies, e.g., phase change memory (PCM) have begun to emerge and will be integrated into the memory hierarchy sooner than later, leading to non-uniform memory access (NUMA) hierarchies. This will make the cost of accessing main memory even higher. In previous years, most of the focus has been on deciding the memory hierarchy level where data must be placed (L1 or L2 caches, main memory, disk, etc.). However, in modern and future generations, each level is getting bigger and its design is being subjected to a number of constraints (wire delays, power budget, etc.). It is becoming very important to make an intelligent decision about where data must be placed within a level. For example, in a large non-uniform access cache (NUCA), we must figure out the optimal bank. Similarly, in a multi-dual inline memory module (DIMM) non uniform memory access (NUMA) main memory, we must figure out the DIMM that is the optimal home for every data page. Studies have indicated that heterogeneous main memory hierarchies that incorporate multiple memory technologies are on the horizon. We must develop solutions for data management that take heterogeneity into account. For these memory organizations, we must again identify the appropriate home for data. In this dissertation, we attempt to verify the following thesis statement: "Can low-complexity hardware and OS mechanisms manage data placement within each memory hierarchy level to optimize metrics such as performance and/or throughput?" In this dissertation we argue for a hardware-software codesign approach to tackle the above mentioned problems at different levels of the memory hierarchy. The proposed methods utilize techniques like page coloring and shadow addresses and are able to handle a large number of problems ranging from managing wire-delays in large, shared NUCA caches to distributing shared capacity among different cores. We then examine data-placement issues in NUMA main memory for a many-core processor with a moderate number of on-chip memory controllers. Using codesign approaches, we achieve efficient data placement by modifying the operating system's (OS) page allocation algorithm for a wide variety of main memory architectures

Jenga: Harnessing Heterogeneous Memories through Reconfigurable Cache Hierarchies

Conventional memory systems are organized as a rigid hierarchy, with multiple levels of progressively larger and slower memories. Hierarchy allows a simple, fixed design to benefit a wide range of applications, because working sets settle at the smallest (and fastest) level they fit in. However, rigid hierarchies also cause significant overheads, because each level adds latency and energy even when it does not capture the working set. In emerging systems with heterogeneous memory technologies such as stacked DRAM, these overheads often limit performance and efficiency. We propose Jenga, a reconfigurable cache hierarchy that avoids these pathologies and approaches the performance of a hierarchy optimized for each application. Jenga monitors application behavior and dynamically builds virtual cache hierarchies out of heterogeneous, distributed cache banks. Jenga uses simple hardware support and a novel software runtime to configure virtual cache hierarchies. On a 36-core CMP with a 1 GB stacked-DRAM cache, Jenga outperforms a combination of state-of-the-art techniques by 10% on average and by up to 36%, and does so while saving energy, improving system-wide energy-delay product by 29% on average and by up to 96%

Hardware/Software Co-design for Multicore Architectures

Siirretty Doriast

DTM-NUCA: dynamic texture mapping-NUCA for energy-efficient graphics rendering

Modern mobile GPUs integrate an increasing number of shader cores to speedup the execution of graphics workloads. Each core integrates a private Texture Cache to apply texturing effects on objects, which is backed-up by a shared L2 cache. However, as in any other memory hierarchy, such organization produces data replication in the upper levels (i.e., the private Texture Caches) to allow for faster accesses at the expense of reducing their overall effective capacity. E.g., in a mobile GPU with four shader cores, about 84.6% of the requested texture blocks are replicated in at least one of the other private Texture Caches. This paper proposes a novel dynamically-mapped NonUniform Cache Architecture (NUCA) organization for the private Texture Caches of a mobile GPU aimed at increasing their effective overall capacity and decreasing the overall access latency by attacking data replication. A block missing in a local Texture Cache may be serviced by a remote one at a cost smaller than a round trip to the shared L2. The proposed Dynamic Texture Mapping-NUCA (DTM-NUCA) features a lightweight mapping table, called Affinity Table, that is independent of the L2 cache size, unlike a traditional NUCA organization. The best owner for a given set of blocks is dynamically determined and stored in the Affinity Table to maximize local accesses. The mechanism also allows for a certain amount of replication to favor local accesses where appropriate, without hurting performance due to the small capacity loss resulting from the allowed replication. DTM-NUCA is presented in two flavors. One with a centralized Affinity Table, and another with a distributed Affinity Table. Experimental results show first that the L2 pressure is effectively reduced, eliminating 41.8% of the L2 accesses on average. As for the average latency, DTM-NUCA performs a very effective job at maximizing local over remote accesses, achieving 73.8% of local accesses on average. As a consequence, our novel DTM-NUCA organization obtains an average speedup of 16.9% and overall 7.6% energy savings over a conventional organization.This work has been supported by the CoCoUnit ERC Advanced Grant of the EU’s Horizon 2020 program (grant No 833057), the Spanish State Research Agency (MCIN/AEI) under grant PID2020-113172RB-I00, the ICREA Academia program and a research fellowship from the University of Murcia’s “Plan Propio de Investigacion”.Peer ReviewedPostprint (author's final draft

The ZCache: Decoupling Ways and Associativity

Abstract—The ever-increasing importance of main memory latency and bandwidth is pushing CMPs towards caches with higher capacity and associativity. Associativity is typically im-proved by increasing the number of ways. This reduces conflict misses, but increases hit latency and energy, placing a stringent trade-off on cache design. We present the zcache, a cache design that allows much higher associativity than the number of physical ways (e.g. a 64-associative cache with 4 ways). The zcache draws on previous research on skew-associative caches and cuckoo hashing. Hits, the common case, require a single lookup, incurring the latency and energy costs of a cache with a very low number of ways. On a miss, additional tag lookups happen off the critical path, yielding an arbitrarily large number of replacement candidates for the incoming block. Unlike conventional designs, the zcache provides associativity by increasing the number of replacement candidates, but not the number of cache ways. To understand the implications of this approach, we develop a general analysis framework that allows to compare associativity across different cache designs (e.g. a set-associative cache and a zcache) by representing associativity as a probability distribution. We use this framework to show that for zcaches, associativity depends only on the number of replacement candidates, and is independent of other factors (such as the number of cache ways or the workload). We also show that, for the same number of replacement candidates, the associativity of a zcache is superior than that of a set-associative cache for most workloads. Finally, we perform detailed simulations of multithreaded and multiprogrammed workloads on a large-scale CMP with zcache as the last-level cache. We show that zcaches provide higher performance and better energy efficiency than conventional caches without incurring the overheads of designs with a large number of ways. I