Design and Implementation of a Radix-100 Division Unit

In this thesis, a novel radix-100 divider is designed and implemented. The proposed divider is 3% faster then the current decimal dividers

Understanding Soft Errors in Uncore Components

The effects of soft errors in processor cores have been widely studied. However, little has been published about soft errors in uncore components, such as memory subsystem and I/O controllers, of a System-on-a-Chip (SoC). In this work, we study how soft errors in uncore components affect system-level behaviors. We have created a new mixed-mode simulation platform that combines simulators at two different levels of abstraction, and achieves 20,000x speedup over RTL-only simulation. Using this platform, we present the first study of the system-level impact of soft errors inside various uncore components of a large-scale, multi-core SoC using the industrial-grade, open-source OpenSPARC T2 SoC design. Our results show that soft errors in uncore components can significantly impact system-level reliability. We also demonstrate that uncore soft errors can create major challenges for traditional system-level checkpoint recovery techniques. To overcome such recovery challenges, we present a new replay recovery technique for uncore components belonging to the memory subsystem. For the L2 cache controller and the DRAM controller components of OpenSPARC T2, our new technique reduces the probability that an application run fails to produce correct results due to soft errors by more than 100x with 3.32% and 6.09% chip-level area and power impact, respectively.Comment: to be published in Proceedings of the 52nd Annual Design Automation Conferenc

Fast speculative address generation and way caching for reducing L1 data cache energy

L1 data caches in high-performance processors continue to grow in set associativity. Higher associativity can significantly increase the cache energy consumption. Cache access latency can be affected as well, leading to an increase in overall energy consumption due to increased execution time. At the same time, the static energy consumption of the cache increases significantly with each new process generation. This paper proposes a new approach to reduce the overall L1 cache energy consumption using a combination of way caching and fast, speculative address generation. A 16-entry way cache storing a 3-bit way number for recently accessed L1 data cache lines is shown sufficient to significantly reduce both static and dynamic energy consumption of the L1 cache. Fast speculative address generation helps to hide the way cache access latency and is highly accurate. The L1 cache energy-delay product is reduced by 10% compared to using the way cache alone and by 37% compared to the use of multiple MRU technique.Peer ReviewedPostprint (published version

Balancing soft error coverage with lifetime reliability in redundantly multithreaded processors

Silicon reliability is a key challenge facing the microprocessor industry. Processors need to be designed such that they are resilient against both soft errors and lifetime reliability phenomena. However, techniques developed to address one class of reliability problems may impact other aspects of silicon reliability. In this paper, we show that Redundant Multi-Threading (RMT), which provides soft error protection, exacerbates lifetime reliability. We then explore two different architectural approaches to tackle this problem, namely, Dynamic Voltage Scaling (DVS) and partial RMT. We show that each approach has certain strengths and weaknesses with respect to performance, soft error coverage, and lifetime reliability. We then propose and evaluate a hybrid approach that combines DVS and partial RMT. We show that this approach provides better improvement in lifetime reliability than DVS or partial RMT alone, buys back a significant amount of performance that is lost due to DVS, and provides nearly complete soft error coverage. I

Approaches to multiprocessor error recovery using an on-chip interconnect subsystem

For future multicores, a dedicated interconnect subsystem for on-chip monitors was found to be highly beneficial in terms of scalability, performance and area. In this thesis, such a monitor network (MNoC) is used for multicores to support selective error identification and recovery and maintain target chip reliability in the context of dynamic voltage and frequency scaling (DVFS). A selective shared memory multiprocessor recovery is performed using MNoC in which, when an error is detected, only the group of processors sharing an application with the affected processors are recovered. Although the use of DVFS in contemporary multicores provides significant protection from unpredictable thermal events, a potential side effect can be an increased processor exposure to soft errors. To address this issue, a flexible fault prevention and recovery mechanism has been developed to selectively enable a small amount of per-core dual modular redundancy (DMR) in response to increased vulnerability, as measured by the processor architectural vulnerability factor (AVF). Our new algorithm for DMR deployment aims to provide a stable effective soft error rate (SER) by using DMR in response to DVFS caused by thermal events. The algorithm is implemented in real-time on the multicore using MNoC and controller which evaluates thermal information and multicore performance statistics in addition to error information. DVFS experiments with a multicore simulator using standard benchmarks show an average 6% improvement in overall power consumption and a stable SER by using selective DMR versus continuous DMR deployment

A low-area reference-free power supply sensor

Power supply unpredictable uctuations jeopardize the functioning of several types of current electronic systems. This work presents a power supply sensor based on a voltage divider followed by buffer-comparator cells employing just MOSFET transistors and provides a digital output. The divider outputs are designed to change more slowly than the thresholds of the comparators, in this way the sensor is able to detect voltage droops. The sensor is implemented in a 65nm technology node occupying an area of 2700?m2 and displaying a power consumption of 50?W. It is designed to work with no voltage reference and with no clock and aiming to obtain a fast response

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

Systematic energy characterization of CMP/SMT processor systems via automated micro-benchmarks

Microprocessor-based systems today are composed of multi-core, multi-threaded processors with complex cache hierarchies and gigabytes of main memory. Accurate characterization of such a system, through predictive pre-silicon modeling and/or diagnostic postsilicon measurement based analysis are increasingly cumbersome and error prone. This is especially true of energy-related characterization studies. In this paper, we take the position that automated micro-benchmarks generated with particular objectives in mind hold the key to obtaining accurate energy-related characterization. As such, we first present a flexible micro-benchmark generation framework (MicroProbe) that is used to probe complex multi-core/multi-threaded systems with a variety and range of energy-related queries in mind. We then present experimental results centered around an IBM POWER7 CMP/SMT system to demonstrate how the systematically generated micro-benchmarks can be used to answer three specific queries: (a) How to project application-specific (and if needed, phase-specific) power consumption with component-wise breakdowns? (b) How to measure energy-per-instruction (EPI) values for the target machine? (c) How to bound the worst-case (maximum) power consumption in order to determine safe, but practical (i.e. affordable) packaging or cooling solutions? The solution approaches to the above problems are all new. Hardware measurement based analysis shows superior power projection accuracy (with error margins of less than 2.3% across SPEC CPU2006) as well as max-power stressing capability (with 10.7% increase in processor power over the very worst-case power seen during the execution of SPEC CPU2006 applications).Peer ReviewedPostprint (author’s final draft