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

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 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

Algorithms and architectures for decimal transcendental function computation

Nowadays, there are many commercial demands for decimal floating-point (DFP) arithmetic operations such as financial analysis, tax calculation, currency conversion, Internet based applications, and e-commerce. This trend gives rise to further development on DFP arithmetic units which can perform accurate computations with exact decimal operands. Due to the significance of DFP arithmetic, the IEEE 754-2008 standard for floating-point arithmetic includes it in its specifications. The basic decimal arithmetic unit, such as decimal adder, subtracter, multiplier, divider or square-root unit, as a main part of a decimal microprocessor, is attracting more and more researchers' attentions. Recently, the decimal-encoded formats and DFP arithmetic units have been implemented in IBM's system z900, POWER6, and z10 microprocessors. Increasing chip densities and transistor count provide more room for designers to add more essential functions on application domains into upcoming microprocessors. Decimal transcendental functions, such as DFP logarithm, antilogarithm, exponential, reciprocal and trigonometric, etc, as useful arithmetic operations in many areas of science and engineering, has been specified as the recommended arithmetic in the IEEE 754-2008 standard. Thus, virtually all the computing systems that are compliant with the IEEE 754-2008 standard could include a DFP mathematical library providing transcendental function computation. Based on the development of basic decimal arithmetic units, more complex DFP transcendental arithmetic will be the next building blocks in microprocessors. In this dissertation, we researched and developed several new decimal algorithms and architectures for the DFP transcendental function computation. These designs are composed of several different methods: 1) the decimal transcendental function computation based on the table-based first-order polynomial approximation method; 2) DFP logarithmic and antilogarithmic converters based on the decimal digit-recurrence algorithm with selection by rounding; 3) a decimal reciprocal unit using the efficient table look-up based on Newton-Raphson iterations; and 4) a first radix-100 division unit based on the non-restoring algorithm with pre-scaling method. Most decimal algorithms and architectures for the DFP transcendental function computation developed in this dissertation have been the first attempt to analyze and implement the DFP transcendental arithmetic in order to achieve faithful results of DFP operands, specified in IEEE 754-2008. To help researchers evaluate the hardware performance of DFP transcendental arithmetic units, the proposed architectures based on the different methods are modeled, verified and synthesized using FPGAs or with CMOS standard cells libraries in ASIC. Some of implementation results are compared with those of the binary radix-16 logarithmic and exponential converters; recent developed high performance decimal CORDIC based architecture; and Intel's DFP transcendental function computation software library. The comparison results show that the proposed architectures have significant speed-up in contrast to the above designs in terms of the latency. The algorithms and architectures developed in this dissertation provide a useful starting point for future hardware-oriented DFP transcendental function computation researches

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

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

A 1.2-V 10- µW NPN-Based Temperature Sensor in 65-nm CMOS With an Inaccuracy of 0.2 °C (3σ) From 70 °C to 125 °C

An NPN-based temperature sensor with digital output transistors has been realized in a 65-nm CMOS process. It achieves a batch-calibrated inaccuracy of ±0.5 ◦C (3¾) and a trimmed inaccuracy of ±0.2 ◦C (3¾) over the temperature range from −70 ◦C to 125 ◦C. This performance is obtained by the use of NPN transistors as sensing elements, the use of dynamic techniques, i.e. correlated double sampling and dynamic element matching, and a single room-temperature trim. The sensor draws 8.3 μA from a 1.2-V supply and occupies an area of 0.1 mm2