Empirical and Statistical Application Modeling Using on -Chip Performance Monitors.

To analyze the performance of applications and architectures, both programmers and architects desire formal methods to explain anomalous behavior. To this end, we present various methods that utilize non-intrusive, performance-monitoring hardware only recently available on microprocessors to provide further explanations of observed behavior. All the methods attempt to characterize and explain the instruction-level parallelism achieved by codes on different architectures. We also present a prototype tool automating the analysis process to exploit the advantages of the empirical and statistical methods proposed. The empirical, statistical and hybrid methods are discussed and explained with case study results provided. The given methods further the wealth of tools available to programmer\u27s and architects for generally understanding the performance of scientific applications. Specifically, the models and tools presented provide new methods for evaluating and categorizing application performance. The empirical memory model serves to quantify the hierarchical memory performance of applications by inferring the incurred latencies of codes after the effect of latency hiding techniques are realized. The instruction-level model and its extensions model on-chip performance analytically giving insight into inherent performance bottlenecks in superscalar architectures. The statistical model and its hybrid extension provide other methods of categorizing codes via their statistical variations. The PTERA performance tool automates the use of performance counters for use by these methods across platforms making the modeling process easier still. These unique methods provide alternatives to performance modeling and categorizing not available previously in an attempt to utilize the inherent modeling capabilities of performance monitors on commodity processors for scientific applications

FIFTY YEARS OF MICROPROCESSOR EVOLUTION: FROM SINGLE CPU TO MULTICORE AND MANYCORE SYSTEMS

Nowadays microprocessors are among the most complex electronic systems that man has ever designed. One small silicon chip can contain the complete processor, large memory and logic needed to connect it to the input-output devices. The performance of today's processors implemented on a single chip surpasses the performance of a room-sized supercomputer from just 50 years ago, which cost over $ 10 million [1]. Even the embedded processors found in everyday devices such as mobile phones are far more powerful than computer developers once imagined. The main components of a modern microprocessor are a number of general-purpose cores, a graphics processing unit, a shared cache, memory and input-output interface and a network on a chip to interconnect all these components [2]. The speed of the microprocessor is determined by its clock frequency and cannot exceed a certain limit. Namely, as the frequency increases, the power dissipation increases too, and consequently the amount of heating becomes critical. So, silicon manufacturers decided to design new processor architecture, called multicore processors [3]. With aim to increase performance and efficiency these multiple cores execute multiple instructions simultaneously. In this way, the amount of parallel computing or parallelism is increased [4]. In spite of mentioned advantages, numerous challenges must be addressed carefully when more cores and parallelism are used.This paper presents a review of microprocessor microarchitectures, discussing their generations over the past 50 years. Then, it describes the currently used implementations of the microarchitecture of modern microprocessors, pointing out the specifics of parallel computing in heterogeneous microprocessor systems. To use efficiently the possibility of multi-core technology, software applications must be multithreaded. The program execution must be distributed among the multi-core processors so they can operate simultaneously. To use multi-threading, it is imperative for programmer to understand the basic principles of parallel computing and parallel hardware. Finally, the paper provides details how to implement hardware parallelism in multicore systems

Energy savings techniques in out-of-order pipeline through value approximation of instructions with data dependencies

Approximate computing has emerged as one of the areas studied over the past few years to improve the performance and energy consumption computers. Approximate computing tolerates imprecision during computation, and it produces data values that are close to the actual outputs obtained from exact computation. From software to circuit level, approximate computing techniques have been applied across all computing domains. This study was carried out on microarchitectural level, where dependencies between two instructions are relaxed in the scheduling unit. This research proposed a technique that allows dependent instructions to execute without waiting for values produced by their producer instructions. This process enabled schedulers to skip certain pipeline processes such operand rename lookup, and instruction wake-up in the instruction scheduler queue to provide additional energy savings. The results of this work revealed an average performance acceleration of 1.25x. In addition, the total of energy savings was achieved at 4.6% for approximation cases that produced tolerable error at the output

Mechanistic analytical modeling of superscalar in-order processor performance

Superscalar in-order processors form an interesting alternative to out-of-order processors because of their energy efficiency and lower design complexity. However, despite the reduced design complexity, it is nontrivial to get performance estimates or insight in the application--microarchitecture interaction without running slow, detailed cycle-level simulations, because performance highly depends on the order of instructions within the application’s dynamic instruction stream, as in-order processors stall on interinstruction dependences and functional unit contention. To limit the number of detailed cycle-level simulations needed during design space exploration, we propose a mechanistic analytical performance model that is built from understanding the internal mechanisms of the processor. The mechanistic performance model for superscalar in-order processors is shown to be accurate with an average performance prediction error of 3.2% compared to detailed cycle-accurate simulation using gem5. We also validate the model against hardware, using the ARM Cortex-A8 processor and show that it is accurate within 10% on average. We further demonstrate the usefulness of the model through three case studies: (1) design space exploration, identifying the optimum number of functional units for achieving a given performance target; (2) program--machine interactions, providing insight into microarchitecture bottlenecks; and (3) compiler--architecture interactions, visualizing the impact of compiler optimizations on performance

Vector support for multicore processors with major emphasis on configurable multiprocessors

It recently became increasingly difficult to build higher speed uniprocessor chips because of performance degradation and high power consumption. The quadratically increasing circuit complexity forbade the exploration of more instruction-level parallelism (JLP). To continue raising the performance, processor designers then focused on thread-level parallelism (TLP) to realize a new architecture design paradigm. Multicore processor design is the result of this trend. It has proven quite capable in performance increase and provides new opportunities in power management and system scalability. But current multicore processors do not provide powerful vector architecture support which could yield significant speedups for array operations while maintaining arealpower efficiency. This dissertation proposes and presents the realization of an FPGA-based prototype of a multicore architecture with a shared vector unit (MCwSV). FPGA stands for Filed-Programmable Gate Array. The idea is that rather than improving only scalar or TLP performance, some hardware budget could be used to realize a vector unit to greatly speedup applications abundant in data-level parallelism (DLP). To be realistic, limited by the parallelism in the application itself and by the compiler\u27s vectorizing abilities, most of the general-purpose programs can only be partially vectorized. Thus, for efficient resource usage, one vector unit should be shared by several scalar processors. This approach could also keep the overall budget within acceptable limits. We suggest that this type of vector-unit sharing be established in future multicore chips. The design, implementation and evaluation of an MCwSV system with two scalar processors and a shared vector unit are presented for FPGA prototyping. The MicroBlaze processor, which is a commercial IP (Intellectual Property) core from Xilinx, is used as the scalar processor; in the experiments the vector unit is connected to a pair of MicroBlaze processors through standard bus interfaces. The overall system is organized in a decoupled and multi-banked structure. This organization provides substantial system scalability and better vector performance. For a given area budget, benchmarks from several areas show that the MCwSV system can provide significant performance increase as compared to a multicore system without a vector unit. However, a MCwSV system with two MicroBlazes and a shared vector unit is not always an optimized system configuration for various applications with different percentages of vectorization. On the other hand, the MCwSV framework was designed for easy scalability to potentially incorporate various numbers of scalar/vector units and various function units. Also, the flexibility inherent to FPGAs can aid the task of matching target applications. These benefits can be taken into account to create optimized MCwSV systems for various applications. So the work eventually focused on building an architecture design framework incorporating performance and resource management for application-specific MCwSV (AS-MCwSV) systems. For embedded system design, resource usage, power consumption and execution latency are three metrics to be used in design tradeoffs. The product of these metrics is used here to choose the MCwSV system with the smallest value

Fast thread communication and synchronization mechanisms for a scalable single chip multiprocessor

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.Includes bibliographical references (p. 159-163).by Stephen William Keckler.Ph.D

Processor evaluation for low power frequency converter product family

Tässä työssä tutkitaan markkinoilla olevia tai lähitulevaisuudessa markkinoille saapuvia prosessoreja käytettäväksi pienitehoisissa taajuusmuuttajissa. Tutkimuksen tarkoitus on selvittää prosessorin sopivuutta sovellukseen, jossa hinta on merkittävä tekijä. Tutkimuksessa esitettyjen vaatimusten perusteella houkuttelevimmat prosessorit otetaan tarkempaan tutkimukseen. Tarkemman selvityksen jälkeen vaatimuksia teknisesti mahdollisimman tarkasti vastaavat prosessorit pyydettiin valmistajalta testattavaksi. Testaaminen suoritettiin lopulta viidelle eri prosessorille, joista kaksi perustui samaan ytimeen. Testaamisen tavoitteena on selvittää prosessorin sopivuus käyttökohteeseensa. Sopivuus testattiin suorittamalla prosessoreissa taajuusmuuttajakäyttöä mallintavaa testikoodia. Tuloksina testikoodin ajamisesta saatiin tietyissä aliohjelmissa kulutettu aika sekä kulutetut kellosyklit. Suorituskyvyn lisäksi testaukseen kuului prosessorikohtaisen kääntäjän aikaansaaman koodin koko. Aliohjelmat sisälsivät sekä aritmeettisia, että loogisia operaatioita, joiden kombinaationa mahdollisimman hyvä sopivuus saatiin selvitettyä.The aim of this thesis is to study processors to be used in a low power frequency converter. Processors under investigation must be currently or in the near future in the market. The purpose is to examine suitability of a processor to an application in which price is an essential factor. The requirements presented in this study will determine which processor will be reviewed more closely. After a precise review, processor vendors was asked to provide as corresponding device as possible to a test. Testing was accomplished eventually with five different processors of which two were based on a same core. The aim of the testing was to investigate suitability of the processors to their target task. Suitability was tested by executing code that models frequency converter application. As a result, spent time and clock cycles are presented in certain functions. In addition to performance, the testing included evaluation of the size of the output code the compilers created. Functions under test consisted of a combination of arithmetic and logic operations that was used to interpret the suitability of the processor