Datacenter Design for Future Cloud Radio Access Network.

Cloud radio access network (C-RAN), an emerging cloud service that combines the traditional radio access network (RAN) with cloud computing technology, has been proposed as a solution to handle the growing energy consumption and cost of the traditional RAN. Through aggregating baseband units (BBUs) in a centralized cloud datacenter, C-RAN reduces energy and cost, and improves wireless throughput and quality of service. However, designing a datacenter for C-RAN has not yet been studied. In this dissertation, I investigate how a datacenter for C-RAN BBUs should be built on commodity servers. I first design WiBench, an open-source benchmark suite containing the key signal processing kernels of many mainstream wireless protocols, and study its characteristics. The characterization study shows that there is abundant data level parallelism (DLP) and thread level parallelism (TLP). Based on this result, I then develop high performance software implementations of C-RAN BBU kernels in C++ and CUDA for both CPUs and GPUs. In addition, I generalize the GPU parallelization techniques of the Turbo decoder to the trellis algorithms, an important family of algorithms that are widely used in data compression and channel coding. Then I evaluate the performance of commodity CPU servers and GPU servers. The study shows that the datacenter with GPU servers can meet the LTE standard throughput with 4× to 16× fewer machines than with CPU servers. A further energy and cost analysis show that GPU servers can save on average 13× more energy and 6× more cost. Thus, I propose the C-RAN datacenter be built using GPUs as a server platform. Next I study resource management techniques to handle the temporal and spatial traffic imbalance in a C-RAN datacenter. I propose a “hill-climbing” power management that combines powering-off GPUs and DVFS to match the temporal C-RAN traffic pattern. Under a practical traffic model, this technique saves 40% of the BBU energy in a GPU-based C-RAN datacenter. For spatial traffic imbalance, I propose three workload distribution techniques to improve load balance and throughput. Among all three techniques, pipelining packets has the most throughput improvement at 10% and 16% for balanced and unbalanced loads, respectively.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120825/1/qizheng_1.pd

Low Power Processor Architectures and Contemporary Techniques for Power Optimization – A Review

The technological evolution has increased the number of transistors for a given die area significantly and increased the switching speed from few MHz to GHz range. Such inversely proportional decline in size and boost in performance consequently demands shrinking of supply voltage and effective power dissipation in chips with millions of transistors. This has triggered substantial amount of research in power reduction techniques into almost every aspect of the chip and particularly the processor cores contained in the chip. This paper presents an overview of techniques for achieving the power efficiency mainly at the processor core level but also visits related domains such as buses and memories. There are various processor parameters and features such as supply voltage, clock frequency, cache and pipelining which can be optimized to reduce the power consumption of the processor. This paper discusses various ways in which these parameters can be optimized. Also, emerging power efficient processor architectures are overviewed and research activities are discussed which should help reader identify how these factors in a processor contribute to power consumption. Some of these concepts have been already established whereas others are still active research areas. © 2009 ACADEMY PUBLISHER

Combining dynamic and static scheduling in high-level synthesis

Field Programmable Gate Arrays (FPGAs) are starting to become mainstream devices for custom computing, particularly deployed in data centres. However, using these FPGA devices requires familiarity with digital design at a low abstraction level. In order to enable software engineers without a hardware background to design custom hardware, high-level synthesis (HLS) tools automatically transform a high-level program, for example in C/C++, into a low-level hardware description. A central task in HLS is scheduling: the allocation of operations to clock cycles. The classic approach to scheduling is static, in which each operation is mapped to a clock cycle at compile time, but recent years have seen the emergence of dynamic scheduling, in which an operation’s clock cycle is only determined at run-time. Both approaches have their merits: static scheduling can lead to simpler circuitry and more resource sharing, while dynamic scheduling can lead to faster hardware when the computation has a non-trivial control flow. This thesis proposes a scheduling approach that combines the best of both worlds. My idea is to use existing program analysis techniques in software designs, such as probabilistic analysis and formal verification, to optimize the HLS hardware. First, this thesis proposes a tool named DASS that uses a heuristic-based approach to identify the code regions in the input program that are amenable to static scheduling and synthesises them into statically scheduled components, also known as static islands, leaving the top-level hardware dynamically scheduled. Second, this thesis addresses a problem of this approach: that the analysis of static islands and their dynamically scheduled surroundings are separate, where one treats the other as black boxes. We apply static analysis including dependence analysis between static islands and their dynamically scheduled surroundings to optimize the offsets of static islands for high performance. We also apply probabilistic analysis to estimate the performance of the dynamically scheduled part and use this information to optimize the static islands for high area efficiency. Finally, this thesis addresses the problem of conservatism in using sequential control flow designs which can limit the throughput of the hardware. We show this challenge can be solved by formally proving that certain control flows can be safely parallelised for high performance. This thesis demonstrates how to use automated formal verification to find out-of-order loop pipelining solutions and multi-threading solutions from a sequential program.Open Acces

Compiler Discovered Dynamic Scheduling of Irregular Code in High-Level Synthesis

Dynamically scheduled high-level synthesis (HLS) achieves higher throughput than static HLS for codes with unpredictable memory accesses and control flow. However, excessive dataflow scheduling results in circuits that use more resources and have a slower critical path, even when only a part of the circuit exhibits dynamic behavior. Recent work has shown that marking parts of a dataflow circuit for static scheduling can save resources and improve performance (hybrid scheduling), but the dynamic part of the circuit still bottlenecks the critical path. We propose instead to selectively introduce dynamic scheduling into static HLS. This paper presents an algorithm for identifying code regions amenable to dynamic scheduling and shows a methodology for introducing dynamically scheduled basic blocks, loops, and memory operations into static HLS. Our algorithm is informed by modulo-scheduling and can be integrated into any modulo-scheduled HLS tool. On a set of ten benchmarks, we show that our approach achieves on average an up to 3.7$\times$ and 3$\times$ speedup against dynamic and hybrid scheduling, respectively, with an area overhead of 1.3$\times$ and frequency degradation of 0.74$\times$ when compared to static HLS.Comment: To appear in the 33rd International Conference on Field-Programmable Logic and Applications (2023

Accelerating Halide on an FPGA by using CIRCT and Calyx as an intermediate step to go from a high-level and software-centric IRs down to RTL

Image processing and, more generally, array processing play an essential role in modern life: from applying filters to the images that we upload to social media to running object detection algorithms on self-driving cars. Optimizing these algorithms can be complex and often results in non-portable code. The Halide language provides a simple way to write image and array processing algorithms by separating the algorithm definition (what needs to be executed) from its execution schedule (how it is executed), delivering state-of-the-art performance that exceeds hand-tuned parallel and vectorized code. Due to the inherent parallel nature of these algorithms, FPGAs present an attractive acceleration platform. While previous work has added an RTL code generator to Halide, and utilized other heterogeneous computing languages as an intermediate step, these projects are no longer maintained. MLIR is an attractive solution, allowing the generation of code that can target multiple devices, such as parallelized and vectorized CPU code, OpenMP, and CUDA. CIRCT builds on top of MLIR to convert generic MLIR code to register transfer level (RTL) languages by using Calyx, a new intermediate language (IL) for compiling high-level programs into hardware designs. This thesis presents a novel flow that implements an MLIR code generator for Halide that generates RTL code, adding the necessary wrappers to execute that code on Xilinx FPGA devices. Additionally, it implements a Halide runtime using the Xilinx Runtime (XRT), enabling seamless execution of the generated Halide RTL kernels. While this thesis provides initial support for running Halide kernels and not all features and optimizations are supported, it also details the future work needed to improve the performance of the generated RTL kernels. The proposed flow serves as a foundation for further research and development in the field of hardware acceleration for image and array processing applications using Halide

Smart memory management through locality analysis

Las memorias caché fueron incorporadas en los microprocesadores ya desde los primeros tiempos, y representan la solución más común para tratar la diferencia de velocidad entre el procesador y la memoria. Sin embargo, muchos estudios señalan que la capacidad de almacenamiento de la caché es malgastada muchas veces, lo cual tiene un impacto directo en el rendimiento del procesador. Aunque una caché está diseñada para explotar diferentes tipos de localidad, todas la referencias a memoria son tratadas de la misma forma, ignorando comportamientos particulares de localidad. El uso restringido de la información de localidad para cada acceso a memoria puede limitar la eficiencia de la cache. En esta tesis se demuestra como un análisis de localidad de datos puede ayudar al investigador a entender dónde y porqué ocurren los fallos de caché, y proponer entonces diferentes técnicas que hacen uso de esta información con el objetivo de mejorar el rendimiento de la memoria caché. Proponemos técnicas en las cuales la información de localidad obtenida por el analizador de localidad es pasada desde el compilador al hardware a través del ISA para guiar el manejo de los accesos a memoria.Hemos desarrollado un análisis estático de localidad de datos. Este análisis está basado en los vectores de reuso y contiene los tres típicos pasos: reuso, volumen y análisis de interferencias. Comparado con trabajos previos, tanto el análisis de volúmenes como el de interferencias ha sido mejorado utilizando información de profiling así como un análisis de interferencias más preciso. El analizador de localidad de datos propuesto ha sido incluido como un paso más en un compilador de investigación. Los resultados demuestran que, para aplicaciones numéricas, el análisis es muy preciso y el overhead de cálculo es bajo. Este análisis es la base para todas las otras partes de la tesis. Además, para algunas propuestas en la última parte de la tesis, hemos usado un análisis de localidad de datos basado en las ecuaciones de fallos de cache. Este análisis, aunque requiere más tiempo de cálculo, es más preciso y más apropiado para cachés asociativas por conjuntos. El uso de dos análisis de localidad diferentes también demuestra que las propuestas arquitectónicas de esta tesis son independientes del análisis de localidad particular utilizado.Después de mostrar la precisión del análisis, lo hemos utilizado para estudiar el comportamiento de localidad exhibido por los programas SPECfp95. Este tipo de análisis es necesario antes de proponer alguna nueva técnica ya que ayuda al investigador a entender porqué ocurren los fallos de caché. Se muestra que con el análisis propuesto se puede estudiar de forma muy precisa la localidad de un programa y detectar donde estan los "puntos negros" así como la razón de estos fallos en cache. Este estudio del comportamiento de localidad de diferentes programas es la base y motivación para las diferentes técnicas propuestas en esta tesis para mejorar el rendimiento de la memoria.Así, usando el análisis de localidad de datos y basándonos en los resultados obtenidos después de analizar el comportamiento de localidad de un conjunto de programas, proponemos utilizar este análisis con el objetivo de guiar tres técnicas diferentes: (i) manejo de caches multimódulo, (ii) prebúsqueda software para bucles con planificación módulo, y (iii) planificación de instrucciones de arquitecturas VLIW clusterizadas.El primer uso del análisis de localidad propuesto es el manejo de una novedosa organización de caché. Esta caché soporta bypass y/o está compuesta por diferentes módulos, cada uno orientado a explotar un tipo particular de localidad. La mayor diferencia de esta caché con respecto propuestas previas es que la decisión de "cachear" o no, o en qué módulo un nuevo bloque es almacenado, está controlado por algunos bits en las instrucciones de memoria ("pistas" de localidad). Estas "pistas" (hints) son fijadas en tiempo de compilación utilizando el análisis de localidad propuesto. Así, la complejidad del manejo de esta caché se mantiene bajo ya que no requiere ningún hardware adicional. Los resultados demuestran que cachés más pequeñas con un manejo más inteligente pueden funcionar tan bien (o mejor) que cachés convencionales más grandes.Hemos utilizado también el análisis de localidad para estudiar la interacción entre la segmentación software y la prebúsqueda software. La segmentación software es una técnica muy efectiva para la planificación de código en bucles (principalmente en aplicaciones numéricas en procesadores VLIW). El esquema más popular de prebúsqueda software se llama planificación módulo. Muchos trabajos sobre planificación módulo se pueden encontrar en la literatura, pero casi todos ellos consideran una suposición crítica: consideran un comportamiento optimista de la cache (en otras palabras, usan siempre la latencia de acierto cuando planifican instrucciones de memoria). Así, los resultados que presentan ignoran los efectos del bloqueo debido a dependencias con instrucciones de memoria. En esta parte de la tesis mostramos que esta suposición puede llevar a planificaciones cuyo rendimiento es bastante más bajo cuando se considera una memoria real. Nosotros proponemos un algoritmo para planificar instrucciones de memoria en bucles con planificación módulo. Hemos estudiado diferentes estrategias de prebúsqueda software y finalmente hemos propuesto un algoritmo que realiza prebúsqueda basándose en el análisis de localidad y en la forma del grafo de dependencias del bucle. Los resultados obtenidos demuestran que el esquema propuesto mejora el rendimiento de las otras heurísticas ya que obtiene un mejor compromiso entre tiempo de cálculo y de bloqueo.Finalmente, el último uso del análisis de localidad estudiado en esta tesis es para guiar un planificador de instrucciones para arquitecturas VLIW clusterizadas. Las arquitecturas clusterizadas están siendo una tendencia común en el diseño de procesadores empotrados/DSP. Típicamente, el núcleo de estos procesadores está basado en un diseño VLIW el cual particiona tanto el banco de registros como las unidades funcionales. En este trabajo vamos un paso más allá y también hacemos la partición de la memoria caché. En este caso, tanto las comunicaciones entre registros como entre memorias han de ser consideradas. Nosotros proponemos un algoritmo que realiza la partición del grafo así como la planificación de instrucciones en un único paso en lugar de hacerlo secuencialmente, lo cual se demuestra que es más efectivo. Este algoritmo es mejorado añadiendo una análisis basado en las ecuaciones de fallos de cache con el objetivo de guiar en la planificación de las instrucciones de memoria para reducir no solo comunicaciones entre registros, sino también fallos de cache.Cache memories were incorporated in microprocessors in the early times and represent the most common solution to deal with the gap between processor and memory speeds. However, many studies point out that the cache storage capacity is wasted many times, which means a direct impact in processor performance. Although a cache is designed to exploit different types of locality, all memory references are handled in the same way, ignoring particular locality behaviors. The restricted use of the locality information for each memory access can limit the effectivity of the cache. In this thesis we show how a data locality analysis can help the researcher to understand where and why cache misses occur, and then to propose different techniques that make use of this information in order to improve the performance of cache memory. We propose techniques in which locality information obtained by the locality analyzer is passed from the compiler to the hardware through the ISA to guide the management of memory accesses.We have developed a static data locality analysis. This analysis is based on reuse vectors and performs the three typical steps: reuse, volume and interfere analysis. Compared with previous works, both volume and interference analysis have been improved by using profile information as well as a more precise inter-ference analysis. The proposed data locality analyzer has been inserted as another pass in a research compiler. Results show that for numerical applications the analysis is very accurate and the computing overhead is low. This analysis is the base for all other parts of the thesis. In addition, for some proposals in the last part of the thesis we have used a data locality analysis based on cache miss equations. This analysis, although more time consuming, is more accurate and more appropriate for set-associative caches. The usage of two different locality analyzers also shows that the architectural proposals of this thesis are independent from the particular locality analysis.After showing the accuracy of the analysis, we have used it to study the locality behavior exhibited by the SPECfp95 programs. This kind of analysis is necessary before proposing any new technique since can help the researcher to understand why cache misses occur. We show that with the proposed analysis we can study very accurately the locality of a program and detect where the hot spots are as well as the reason for these misses. This study of the locality behavior of different programs is the base and motivation for the different techniques proposed in this thesis to improve the memory performance.Thus, using the data locality analysis and based on the results obtained after analyzing the locality behavior of a set of programs, we propose to use this analysis in order to guide three different techniques: (i) management of multi-module caches, (ii) software prefetching for modulo scheduled loops, and (iii) instruction scheduling for clustered VLIW architectures.The first use of the proposed data locality analysis is to manage a novel cache organization. This cache supports bypassing and/or is composed of different modules, each one oriented to exploit a particular type of locality. The main difference of this cache with respect to previous proposals is that the decision of caching or not, or in which module a new fetched block is allocated is managed by some bits in memory instructions (locality hints). These hints are set at compile time using the proposed locality analysis. Thus, the management complexity of this cache is kept low since no additional hardware is required. Results show that smaller caches with a smart management can perform as well as (or better than) bigger conventional caches.We have also used the locality analysis to study the interaction between software pipelining and software prefetching. Software pipelining has been shown to be a very effective scheduling technique for loops (mainly in numerical applications for VLIW processors). The most popular scheme for software pipelining is called modulo scheduling. Many works on modulo scheduling can be found in the literature, but almost all of them make a critical assumption: they consider an optimistic behavior of the cache (in other words, they use the hit latency when a memory instruction is scheduled). Thus, the results they present ignore the effect of stalls due to dependences with memory instructions. In this part of the thesis we show that this assumption can lead to schedules whose performance is rather low when a real memory is considered. Thus, we propose an algorithm to schedule memory instructions in modulo scheduled loops. We have studied different software prefetching strategies and finally proposed an algorithm that performs prefetching based on the locality analysis and the shape of the loop dependence graph. Results obtained shows that the proposed scheme outperforms other heuristic approaches since it achieves a better trade-off between compute and stall time than the others. Finally, the last use of the locality analysis studied in this thesis is to guide an instruction scheduler for a clustered VLIW architecture. Clustered architectures are becoming a common trend in the design of embedded/DSP processors. Typically, the core of these processors is based on a VLIW design which partitionates both register file and functional units. In this work we go a step beyond and also make a partition of the cache memory. Then, both inter-register and inter-memory communications have to be taken into account. We propose an algorithm that performs both graph partition and instruction scheduling in a single step instead of doing it sequentially, which is shown to be more effective. This algorithm is improved by adding an analysis based on the cache miss equations in order to guide the scheduling of memory instructions in clusters with the aim of reducing not only inter-register communications, but also cache misses