Fast simulation techniques for microprocessor design space exploration

Designing a microprocessor is extremely time-consuming. Computer architects heavily rely on architectural simulators, e.g., to drive high-level design decisions during early stage design space exploration. The benefit of architectural simulators is that they yield relatively accurate performance results, are highly parameterizable and are very flexible to use. The downside, however, is that they are at least three or four orders of magnitude slower than real hardware execution. The current trend towards multicore processors exacerbates the problem; as the number of cores on a multicore processor increases, simulation speed has become a major concern in computer architecture research and development. In this dissertation, we propose and evaluate two simulation techniques that reduce the simulation time significantly: statistical simulation and interval simulation. Statistical simulation speeds up the simulation by reducing the number of dynamically executed instructions. First, we collect a number of program execution characteristics into a statistical profile. From this profile we can generate a synthetic trace that exhibits the same execution behavior but which has a much shorter trace length as compared to the original trace. Simulating this synthetic trace then yields a performance estimate. Interval simulation raises the level of abstraction in architectural simulation; it replaces the core-level cycle-accurate simulation model by a mechanistic analytical model. The analytical model builds on insights from interval analysis: miss events divide the smooth streaming of instructions into so called intervals. The model drives the timing by analyzing the type of the miss events and their latencies, instead of tracking the individual instructions as they propagate through the pipeline stages

A comparison of cache hierarchies for SMT processors

In the multithread and multicore era, programs are forced to share part of the processor structures. On one hand, the state of the art in multithreading describes how efficiently manage and distribute inner resources such as reorder buffer or issue windows. On the other hand, there is a substantial body of works focused on outer resources, mainly on how to effectively share last level caches in multicores. Between these ends, first and second level caches have remained apart even if they are shared in most commercial multithreaded processors. This work analyzes multiprogrammed workloads as the worst-case scenario for cache sharing among threads. In order to obtain representative results, we present a sampling-based methodology that for multiple metrics such as STP, ANTT, IPC throughput, or fairness, reduces simulation time up to 4 orders of magnitude when running 8-thread workloads with an error lower than 3% and a confidence level of 97%. With the above mentioned methodology, we compare several state-of-the-art cache hierarchies, and observe that Light NUCA provides performance benefits in SMT processors regardless the organization of the last level cache. Most importantly, Light NUCA gains are consistent across the entire number of simulated threads, from one to eight.Peer ReviewedPostprint (author's final draft

On the problem of evaluating the performance of multiprogrammed workloads

Multithreaded architectures are becoming more and more popular. In order to evaluate their behavior, several methodologies and metrics have been proposed. A methodology defines when the measurements for a given workload execution are taken. A metric combines those measurements to obtain a final evaluation result. However, since current evaluation methodologies do not provide representative measurements for these metrics, the analysis and evaluation of novel ideas could be either unfair or misleading. Given the potential impact of multithreaded architectures on current and future processor designs, it is crucial to develop an accurate evaluation methodology for them. This paper presents FAME, a new evaluation methodology aimed to fairly measure the performance of multithreaded processors executing multiprogrammed workloads. FAME reexecutes all programs in the workload until all of them are fairly represented in the final measurements taken. We compare FAME with previously used methodologies showing that it provides more accurate measurements, becoming an ideal evaluation methodology to analyze proposals for multithreaded architectures.Peer ReviewedPostprint (published version

RPPM : Rapid Performance Prediction of Multithreaded workloads on multicore processors

Analytical performance modeling is a useful complement to detailed cycle-level simulation to quickly explore the design space in an early design stage. Mechanistic analytical modeling is particularly interesting as it provides deep insight and does not require expensive offline profiling as empirical modeling. Previous work in mechanistic analytical modeling, unfortunately, is limited to single-threaded applications running on single-core processors. This work proposes RPPM, a mechanistic analytical performance model for multi-threaded applications on multicore hardware. RPPM collects microarchitecture-independent characteristics of a multi-threaded workload to predict performance on a previously unseen multicore architecture. The profile needs to be collected only once to predict a range of processor architectures. We evaluate RPPM's accuracy against simulation and report a performance prediction error of 11.2% on average (23% max). We demonstrate RPPM's usefulness for conducting design space exploration experiments as well as for analyzing parallel application performance

Adaptive prefetch for multicores

[EN] Current multicore systems implement various hardware prefetchers since prefetching can significantly hide the huge main memory latencies. However, memory bandwidth is a scarce resource which becomes critical with the increasing core count.Therefore, prefetchers must smartly regulate their aggressiveness to make an efficient use of this shared resource. Recent research has proposed to throttle up/down the prefetcher aggressiveness level, considering local and global system information gathered at the memory controller. However, in memory-hungry mixes, keeping active the prefetchers even with the lowest aggressiveness can, in some cases, damage the system performance and increase the energy consumption. This Master's Thesis proposes the ADP prefetcher, which, unlike previous proposals, turns off the prefetcher in specific cores when no local benefits are expected or it is adversely interfering with other cores. The key component of ADP is the activation policy which must foresee when prefetching will be beneficial without the prefetcher being active. The proposed policies are orthogonal to the prefetcher mechanism implemented in the microprocessor. The proposed prefetcher improves both performance and energy with respect to a state-of-the-art adaptive prefetcher in both memory-bandwidth hungry workloads and in workloads combining memory hungry with CPU intensive applications. Compared to a state-of-the-art prefetcher, the proposal almost halves the increase in main memory requests caused by prefetching while improving the performance by 4.46% on average, and with significantly less DRAM energy consumption[ES] Los sistemas multinúcleo actuales implementan diversos mecanismos hardware de prebúsqueda ya que contribuyen a ocultar significativamente las enormes latencias de los accesos a memoria principal. No obstante, el ancho de banda de memoria es un recurso escaso, y se convierte en un importante cuello de botella al incrementarse el número de núcleos. Por lo tanto, los mecanismos de prebúsqueda deben regular inteligentemente su agresividad para hacer un uso eficiente de este recurso compartido. Otro trabajos recientes proponen mecanismos para ajustar el nivel de agresividad del mecanismo de prebúsqueda, teniendo en cuenta tanto información local al núcleo como información global obtenida del controlador de memoria. Sin embargo, en cargas con un gran número de accesos a memoria, mantener activa la prebúsqueda, incluso con los niveles de agresividad más bajos puede, en algunos casos, perjudicar el rendimiento del sistema y aumentar el consumo de energía. Esta Tesina de Master propone ADP, un novedoso mecanismo de prebúsqueda adaptativa que, a diferencia de propuestas anteriores, se desactiva en los núcleos en los que no se espera que mejore las prestaciones o en los que está interfiriendo negativamente con otros núcleos. El componente clave de ADP es la política de activación, ya que debe de ser capaz de prever cuando la prebúsqueda va a aportar beneficios sin que esta esté activa. Además, las políticas propuestas son ortogonales al mecanismo de prebúsqueda implementado en el microprocesador. El mecanismo de prebúsqueda propuesto mejora tanto el rendimiento como el consumo de energía con respecto al estado del arte en prebúsqueda adaptativa, tanto en cargas con un alto consumo de ancho de banda como en cargas que combinan este tipo de cargas con otras que hacen un uso intensivo de la CPU. En comparación, nuestra propuesta reduce prácticamente a la mitad el aumento en los accesos a memoria principal causados por la prebúsqueda. Esta mejora en el rendimiento, de media un 4,46 \%, se consigue con una significativa reducción en el consumo de energía. (español) Current multicore systems implement various hardware prefetchers since prefetching can significantly hide the huge main memory latencies. However, memory bandwidth is a scarce resource which becomes critical with the increasing core count.Therefore, prefetchers must smartly regulate their aggressiveness to make an efficient use of this shared resource.Selfa Oliver, V. (2014). Adaptive prefetch for multicores. http://hdl.handle.net/10251/59527Archivo delegad

The multi-program performance model: debunking current practice in multi-core simulation

Composing a representative multi-program multi-core workload is non-trivial. A multi-core processor can execute multiple independent programs concurrently, and hence, any program mix can form a potential multi-program workload. Given the very large number of possible multiprogram workloads and the limited speed of current simulation methods, it is impossible to evaluate all possible multi-program workloads. This paper presents the Multi-Program Performance Model (MPPM), a method for quickly estimating multiprogram multi-core performance based on single-core simulation runs. MPPM employs an iterative method to model the tight performance entanglement between co-executing programs on a multi-core processor with shared caches. Because MPPM involves analytical modeling, it is very fast, and it estimates multi-core performance for a very large number of multi-program workloads in a reasonable amount of time. In addition, it provides confidence bounds on its performance estimates. Using SPEC CPU2006 and up to 16 cores, we report an average performance prediction error of 2.3% and 2.9% for system throughput (STP) and average normalized turnaround time (ANTT), respectively, while being up to five orders of magnitude faster than detailed simulation. Subsequently, we demonstrate that randomly picking a limited number of multi-program workloads, as done in current pactice, can lead to incorrect design decisions in practical design and research studies, which is alleviated using MPPM. In addition, MPPM can be used to quickly identify multi-program workloads that stress multi-core performance through excessive conflict behavior in shared caches; these stress workloads can then be used for driving the design process further

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

A research-oriented course on Advanced Multicore Architecture: Contents and active learning methodologies

[EN] The fast evolution of multicore processors makes it difficult for professors to offer computer architecture courses with updated contents. To deal with this shortcoming that could discourage students, the most appropriate solution is a research-oriented course based on current microprocessor industry trends. Additionally, we also seek to improve the students' skills by applying active learning methodologies, where teachers act as guiders and resource providers while students take the responsibility for their learning. In this paper, we present the Advanced Multicore Architecture (AMA) course, which follows a research-oriented approach to introduce students in architectural breakthroughs and uses active learning methodologies to enable students to develop practical research skills such as critical analysis of research papers or communication abilities. To this end five main activities are used: (i) lectures dealing with key theoretical concepts, (ii) paper review & discussion, (iii) research-oriented practical exercises, (iv) lab sessions with a state-of-the-art multicore simulator, and (v) paper presentation. An important part of all these activities is driven by active learning methodologies. Special emphasis is put on the practical side by allocating 40% of the time to labs and exercises. This work also includes an assessment study that analyzes both the course contents and the used methodology (both of them compared to other courses).This work was supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and by Plan E funds under Grant TIN2014-62246-EXP and Grant TIN2015-66972-C5-1-R, and by Generalitat Valenciana under grant AICO/2016/059. Authors also would like to thank Onur Mutlu for making available online his valuable teaching material.Petit Martí, SV.; Sahuquillo Borrás, J.; Gómez Requena, ME.; Selfa-Oliver, V. (2017). A research-oriented course on Advanced Multicore Architecture: Contents and active learning methodologies. Journal of Parallel and Distributed Computing. 105:63-72. https://doi.org/10.1016/j.jpdc.2017.01.011S637210

A methodology for analyzing commercial processor performance numbers

The wealth of performance numbers provided by benchmarking corporations makes it difficult to detect trends across commercial machines. A proposed methodology, based on statistical data analysis, simplifies exploration of these machines' large datasets

A Research-Oriented Course on Advanced Multicore Architecture

©2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Multicore processors have become ubiquitous in our real life in devices like smartphones, tablets, etc. In fact, they are present in almost all segments of the computing market, from supercomputers to embedded devices. The huge market competence have lead industry and academia to develop vertiginous technological and architectural advances. The fast evolution that are still experiencing current multicores makes difficult for instructors to offer computer architecture courses with updated contents, preferably showing the industry and academia research trends. To deal with this shortcoming, authors consider that a research-oriented course is the most appropriate solution. This paper presents an advanced computer architecture course called Advanced Multicore Architectures, offered in 2015. The course covers the basic topics of multicore architecture and has been organized in four main modules regarding multicore basis, performance evaluation, advanced caching, and main memory organization. The course follows a research-oriented approach that covers theoretical concepts at lectures in which recent research papers are analyzed to provide students a wide view of current trends. Moreover, additional teaching methods like lab sessions with a state-of-the-art multicore simulator or research-oriented exercises have been used with the aim of introducing students to research in these topics. To achieve this fully research-oriented methodology, about 40% of the time is devoted to labs and exercises.This work was supported by the Spanish Ministerio de Economía y Competitividad (MINECO) and by FEDER funds under Grant TIN2012-38341-C04-01, and by the Intel Early Career Faculty Honor Program Award.Sahuquillo Borrás, J.; Petit Martí, SV.; Selfa Oliver, V.; Gómez Requena, ME. (2015). A Research-Oriented Course on Advanced Multicore Architecture. IEEE Computer Society. https://doi.org/10.1109/IPDPSW.2015.46