Optimizing Instruction Scheduling and Register Allocation for Register-File-Connected Clustered VLIW Architectures

Clustering has become a common trend in very long instruction words (VLIW) architecture to solve the problem of area, energy consumption, and design complexity. Register-file-connected clustered (RFCC) VLIW architecture uses the mechanism of global register file to accomplish the inter-cluster data communications, thus eliminating the performance and energy consumption penalty caused by explicit inter-cluster data move operations in traditional bus-connected clustered (BCC) VLIW architecture. However, the limit number of access ports to the global register file has become an issue which must be well addressed; otherwise the performance and energy consumption would be harmed. In this paper, we presented compiler optimization techniques for an RFCC VLIW architecture called Lily, which is designed for encryption systems. These techniques aim at optimizing performance and energy consumption for Lily architecture, through appropriate manipulation of the code generation process to maintain a better management of the accesses to the global register file. All the techniques have been implemented and evaluated. The result shows that our techniques can significantly reduce the penalty of performance and energy consumption due to access port limitation of global register file

Instruction scheduling optimizations for energy efficient VLIW processors

Very Long Instruction Word (VLIW) processors are wide-issue statically scheduled processors. Instruction scheduling for these processors is performed by the compiler and is therefore a critical factor for its operation. Some VLIWs are clustered, a design that improves scalability to higher issue widths while improving energy efficiency and frequency. Their design is based on physically partitioning the shared hardware resources (e.g., register file). Such designs further increase the challenges of instruction scheduling since the compiler has the additional tasks of deciding on the placement of the instructions to the corresponding clusters and orchestrating the data movements across clusters. In this thesis we propose instruction scheduling optimizations for energy-efficient VLIW processors. Some of the techniques aim at improving the existing state-of-theart scheduling techniques, while others aim at using compiler techniques for closing the gap between lightweight hardware designs and more complex ones. Each of the proposed techniques target individual features of energy efficient VLIW architectures. Our first technique, called Aligned Scheduling, makes use of a novel scheduling heuristic for hiding memory latencies in lightweight VLIW processors without hardware load-use interlocks (Stall-On-Miss). With Aligned Scheduling, a software-only technique, a SOM processor coupled with non-blocking caches can better cope with the cache latencies and it can perform closer to the heavyweight designs. Performance is improved by up to 20% across a range of benchmarks from the Mediabench II and SPEC CINT2000 benchmark suites. The rest of the techniques target a class of VLIW processors known as clustered VLIWs, that are more scalable and more energy efficient and operate at higher frequencies than their monolithic counterparts. The second scheme (LUCAS) is an improved scheduler for clustered VLIW processors that solves the problem of the existing state-of-the-art schedulers being very susceptible to the inter-cluster communication latency. The proposed unified clustering and scheduling technique is a hybrid scheme that performs instruction by instruction switching between the two state-of-the-art clustering heuristics, leading to better scheduling than either of them. It generates better performing code compared to the state-of-the-art for a wide range of inter-cluster latency values on the Mediabench II benchmarks. The third technique (called CAeSaR) is a scheduler for clustered VLIW architectures that minimizes inter-cluster communication by local caching and reuse of already received data. Unlike dynamically scheduled processors, where this can be supported by the register renaming hardware, in VLIWs it has to be done by the code generator. The proposed instruction scheduler unifies cluster assignment, instruction scheduling and communication minimization in a single unified algorithm, solving the phase ordering issues between all three parts. The proposed scheduler shows an improvement in execution time of up to 20.3% and 13.8% on average across a range of benchmarks from the Mediabench II and SPEC CINT2000 benchmark suites. The last technique, applies to heterogeneous clustered VLIWs that support dynamic voltage and frequency scaling (DVFS) independently per cluster. In these processors there are no hardware interlocks between clusters to honor the data dependencies. Instead, the scheduler has to be aware of the DVFS decisions to guarantee correct execution. Effectively controlling DVFS, to selectively decrease the frequency of clusters with slack in their schedule, can lead to significant energy savings. The proposed technique (called UCIFF) solves the phase ordering problem between frequency selection and scheduling that is present in existing algorithms. The results show that UCIFF produces better code than the state-of-the-art and very close to the optimal across the Mediabench II benchmarks. Overall, the proposed instruction scheduling techniques lead to either better efficiency on existing designs or allow simpler lightweight designs to be competitive against ones with more complex hardware

Architectural and Complier Mechanisms for Accelerating Single Thread Applications on Mulitcore Processors.

Multicore systems have become the dominant mainstream computing platform. One of the biggest challenges going forward is how to efficiently utilize the ever increasing computational power provided by multicore systems. Applications with large amounts of explicit thread-level parallelism naturally scale performance with the number of cores. However, single-thread applications realize little to no gains from multicore systems. This work investigates architectural and compiler mechanisms to automatically accelerate single thread applications on multicore processors by efficiently exploiting three types of parallelism across multiple cores: instruction level parallelism (ILP), fine-grain thread level parallelism (TLP), and speculative loop level parallelism (LLP). A multicore architecture called Voltron is proposed to exploit different types of parallelism. Voltron can organize the cores for execution in either coupled or decoupled mode. In coupled mode, several in-order cores are coalesced to emulate a wide-issue VLIW processor. In decoupled mode, the cores execute a set of fine-grain communicating threads extracted by the compiler. By executing fine-grain threads in parallel, Voltron provides coarse-grained out-of-order execution capability using in-order cores. Architectural mechanisms for speculative execution of loop iterations are also supported under the decoupled mode. Voltron can dynamically switch between two modes with low overhead to exploit the best form of available parallelism. This dissertation also investigates compiler techniques to exploit different types of parallelism on the proposed architecture. First, this work proposes compiler techniques to manage multiple instruction streams to collectively function as a single logical stream on a conventional VLIW to exploit ILP. Second, this work studies compiler algorithms to extract fine-grain threads. Third, this dissertation proposes a series of systematic compiler transformations and a general code generation framework to expose hidden speculative LLP hindered by register and memory dependences in the code. These transformations collectively remove inter-iteration dependences that are caused by subsets of isolatable instructions, are unwindable, or occur infrequently. Experimental results show that proposed mechanisms can achieve speedups of 1.33 and 1.14 on 4 core machines by exploiting ILP and TLP respectively. The proposed transformations increase the DOALL loop coverage in applications from 27% to 61%, resulting in a speedup of 1.84 on 4 core systems.Ph.D.Computer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/58419/1/hongtaoz_1.pd

A RECONFIGURABLE AND EXTENSIBLE EXPLORATION PLATFORM FOR FUTURE HETEROGENEOUS SYSTEMS

Accelerator-based -or heterogeneous- computing has become increasingly important in a variety of scenarios, ranging from High-Performance Computing (HPC) to embedded systems. While most solutions use sometimes custom-made components, most of today’s systems rely on commodity highend CPUs and/or GPU devices, which deliver adequate performance while ensuring programmability, productivity, and application portability. Unfortunately, pure general-purpose hardware is affected by inherently limited power-efficiency, that is, low GFLOPS-per-Watt, now considered as a primary metric. The many-core model and architectural customization can play here a key role, as they enable unprecedented levels of power-efficiency compared to CPUs/GPUs. However, such paradigms are still immature and deeper exploration is indispensable. This dissertation investigates customizability and proposes novel solutions for heterogeneous architectures, focusing on mechanisms related to coherence and network-on-chip (NoC). First, the work presents a non-coherent scratchpad memory with a configurable bank remapping system to reduce bank conflicts. The experimental results show the benefits of both using a customizable hardware bank remapping function and non-coherent memories for some types of algorithms. Next, we demonstrate how a distributed synchronization master better suits many-cores than standard centralized solutions. This solution, inspired by the directory-based coherence mechanism, supports concurrent synchronizations without relying on memory transactions. The results collected for different NoC sizes provided indications about the area overheads incurred by our solution and demonstrated the benefits of using a dedicated hardware synchronization support. Finally, this dissertation proposes an advanced coherence subsystem, based on the sparse directory approach, with a selective coherence maintenance system which allows coherence to be deactivated for blocks that do not require it. Experimental results show that the use of a hybrid coherent and non-coherent architectural mechanism along with an extended coherence protocol can enhance performance. The above results were all collected by means of a modular and customizable heterogeneous many-core system developed to support the exploration of power-efficient high-performance computing architectures. The system is based on a NoC and a customizable GPU-like accelerator core, as well as a reconfigurable coherence subsystem, ensuring application-specific configuration capabilities. All the explored solutions were evaluated on this real heterogeneous system, which comes along with the above methodological results as part of the contribution in this dissertation. In fact, as a key benefit, the experimental platform enables users to integrate novel hardware/software solutions on a full-system scale, whereas existing platforms do not always support a comprehensive heterogeneous architecture exploration

An automated OpenCL FPGA compilation framework targeting a configurable, VLIW chip multiprocessor

Modern system-on-chips augment their baseline CPU with coprocessors and accelerators to increase overall computational capacity and power efficiency, and thus have evolved into heterogeneous systems. Several languages have been developed to enable this paradigm shift, including CUDA and OpenCL. This thesis discusses a unified compilation environment to enable heterogeneous system design through the use of OpenCL and a customised VLIW chip multiprocessor (CMP) architecture, known as the LE1. An LLVM compilation framework was researched and a prototype developed to enable the execution of OpenCL applications on the LE1 CPU. The framework fully automates the compilation flow and supports work-item coalescing to better utilise the CPU cores and alleviate the effects of thread divergence. This thesis discusses in detail both the software stack and target hardware architecture and evaluates the scalability of the proposed framework on a highly precise cycle-accurate simulator. This is achieved through the execution of 12 benchmarks across 240 different machine configurations, as well as further results utilising an incomplete development branch of the compiler. It is shown that the problems generally scale well with the LE1 architecture, up to eight cores, when the memory system becomes a serious bottleneck. Results demonstrate superlinear performance on certain benchmarks (x9 for the bitonic sort benchmark with 8 dual-issue cores) with further improvements from compiler optimisations (x14 for bitonic with the same configuration

Affordable kilo-instruction processors

Diversos motius expliquen l'estancament en el que es troba el desenvolupament del processador tradicional dissenyat per maximitzar el rendiment d'un únic fil d'execució. Per una banda, técniques agressives com la supersegmentacó del camí de dades o l'execució fora d'ordre tenen un impacte molt negatiu sobre el consum de potència i la complexitat del disseny. Altrament, l'increment en la freqüència del processador augmenta la discrepància entre la velocitat del processador i el temps d'accés a memòria principal. Tot i que les memòries cau redueixen considerablement el nombre d'accessos a memòria principal, aquests accessos introdueixen latencies prou grans per reduir considerablement el rendiment. Tècniques convencionals com l'execució fora d'ordre, útils per ocultar accessos a les memòries cau de 2on nivell, no estan pensades per ocultar latències tan grans. Caldrien cues amb mides de centenars d'instruccions i milers de registres per tal de no interrompre l'execució en el moment de produir-se un accés a memòria principal. Desafortunadament, la tecnologia disponible no és eficient per implementar aquestes estructures monolíticament, doncs resultaria un temps d'accés molt elevat, un consum de potència igualment elevat i un àrea no menyspreable. En aquesta tesi s'han estudiat tècniques que permeten l'implementació d'un processador amb capacitat per continuar processant instruccions en el cas de que es produeixin accessos a memòria principal. Les condicions per a que aquest processador sigui implementable són que estigui basat en estructures de mida convencional i que tingui una unitat de control senzilla. El repte es troba en conciliar un model de processador distribuït amb un control senzill. El problema del disseny del processador s'ha enfocat observant el comportament d'un processador de recursos infinits. S'ha observat que l'execució segueix uns patrons molt interessants, basats en la localitat d'execució. En aplicacions numèriques s'observa que més del 70% de les instruccions no depenen de accessos a memòria principal. Aixó és molt important doncs mostra que sempre hi ha una porció important d'instruccions executables poc després de la decodificació. Aixó permet proposar un nou tipus de processador amb dues unitats d'execució. La primera unitat (el "Cache Processor") processa a alta velocitat instruccions independents de memòria principal. La segona unitat ("Memory Processor") processa les instruccions dependents de accessos a memòria principal, pero de forma molt més relaxada, cosa que li permet mantenir milers de instruccions en vol. Aquesta proposta rep el nom de Decoupled KILO-Instruction Processor (D-KIP) i té forces avantatges: per un costat permet la construcció d'un kilo-instruction processor basat en estructures convencionals i per l'altre simplifica el disseny ja que minimitza les interaccions entre ambdos unitats d'execució.En aquesta tesi es proposen dos implementacions de processadors desacoblats: el D-KIP original, i el Flexible Heterogeneous MultiCore (FMC). Sobre aquestes propostes s'analitza el rendiment i es compara amb altres tècniques que incrementan el parallelisme de memoria, com el prefetching o l'execució "runahead". D'aquesta avaluació es desprén que el processador FMC té un rendiment similar al de un processador convencional amb una finestra de 1500 instruccions en vol. Posteriorment s'analitza l'integració del FMC en entorns multicore/multiprogrammats. La tesi es completa amb la proposta d'una cua de loads i stores (LSQ) per a aquest tipus de processador.Several motives explain the slowdown of high-performance single-thread processor development. On the one hand, aggressive techniques such as superpipelining or out-of-order execution have a considerable impact on power consumption and design complexity. On the other hand, the increment in processor frequencies has led to a large disparity between processor speed and memory access time. Although cache memories considerably reduce the number of accesses to main memory, the remaining accesses introduce latencies large enough to considerably decrease performance. Conventional techniques such as out-of-order execution, while effective in hiding L2 cache accesses, cannot hide latencies this large. Queues of hundreds of entries and thousands of registers would be necessary in order to prevent execution from stalling in the event of a L2 cache miss. Unfortunately, current technology cannot efficiently implement such structures monolithically, as access latencies would considerably increase, as would power consumption and area consumption.In this thesis we studied techniques that allow the processor to continue processing instructions in the event of main memory accesses. The conditions for such a processor to be implementable are that it should be based on structures of conventional size and that it should feature simple control logic. The challenge lies in being able to design a distributed processor with simple control. The design of this processor has been approached by analyzing the behavior of a processor with infinite resources. We have observed that execution follows a very interesting pattern based on execution locality. In numerical codes we observed that over 70% of all instructions do not depend on memory accesses. This is interesting since it shows that there is always a large portion of instructions that can be executed shortly after decode. This allows us to propose a new kind of processor with two execution units. The first unit, the Cache Processor, processes memory-independent instructions at high speed. The second unit, the Memory Processor, processes instructions that depend on main memory accesses, but using relaxed scheduling logic, which allows it to scale to thousands of in-flight instructions. This proposal, which receives the name of Decoupled KILO-Instruction Processor (D-KIP), has several advantages. On the one hand it allows the construction of a kilo-instruction processor based on conventional structures and, on the other hand, it simplifies the design as the interaction between both execution units is minimal. In this thesis two implementations for this kind of processor are presented: the original D-KIP and the Flexible Heterogeneous MultiCore (FMC). The performance of these proposals is analyzed and compared to other proposals that increase memory-level parallelism, such as prefetching or runahead execution. It is observed that the FMC processor performs at the same level of a conventional processor with a window of around 1500 instructions. Further, the integration of the FMC processor into a multicore/multiprogrammed environment is studied. This thesis concludes with the proposal of a two-level Load/Store Queue for this kind of processor

Gestión de jerarquías de memoria híbridas a nivel de sistema

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Arquitectura de Computadoras y Automática y de Ku Leuven, Arenberg Doctoral School, Faculty of Engineering Science, leída el 11/05/2017.In electronics and computer science, the term ‘memory’ generally refers to devices that are used to store information that we use in various appliances ranging from our PCs to all hand-held devices, smart appliances etc. Primary/main memory is used for storage systems that function at a high speed (i.e. RAM). The primary memory is often associated with addressable semiconductor memory, i.e. integrated circuits consisting of silicon-based transistors, used for example as primary memory but also other purposes in computers and other digital electronic devices. The secondary/auxiliary memory, in comparison provides program and data storage that is slower to access but offers larger capacity. Examples include external hard drives, portable flash drives, CDs, and DVDs. These devices and media must be either plugged in or inserted into a computer in order to be accessed by the system. Since secondary storage technology is not always connected to the computer, it is commonly used for backing up data. The term storage is often used to describe secondary memory. Secondary memory stores a large amount of data at lesser cost per byte than primary memory; this makes secondary storage about two orders of magnitude less expensive than primary storage. There are two main types of semiconductor memory: volatile and nonvolatile. Examples of non-volatile memory are ‘Flash’ memory (sometimes used as secondary, sometimes primary computer memory) and ROM/PROM/EPROM/EEPROM memory (used for firmware such as boot programs). Examples of volatile memory are primary memory (typically dynamic RAM, DRAM), and fast CPU cache memory (typically static RAM, SRAM, which is fast but energy-consuming and offer lower memory capacity per are a unit than DRAM). Non-volatile memory technologies in Si-based electronics date back to the 1990s. Flash memory is widely used in consumer electronic products such as cellphones and music players and NAND Flash-based solid-state disks (SSDs) are increasingly displacing hard disk drives as the primary storage device in laptops, desktops, and even data centers. The integration limit of Flash memories is approaching, and many new types of memory to replace conventional Flash memories have been proposed. The rapid increase of leakage currents in Silicon CMOS transistors with scaling poses a big challenge for the integration of SRAM memories. There is also the case of susceptibility to read/write failure with low power schemes. As a result of this, over the past decade, there has been an extensive pooling of time, resources and effort towards developing emerging memory technologies like Resistive RAM (ReRAM/RRAM), STT-MRAM, Domain Wall Memory and Phase Change Memory(PRAM). Emerging non-volatile memory technologies promise new memories to store more data at less cost than the expensive-to build silicon chips used by popular consumer gadgets including digital cameras, cell phones and portable music players. These new memory technologies combine the speed of static random-access memory (SRAM), the density of dynamic random-access memory (DRAM), and the non-volatility of Flash memory and so become very attractive as another possibility for future memory hierarchies. The research and information on these Non-Volatile Memory (NVM) technologies has matured over the last decade. These NVMs are now being explored thoroughly nowadays as viable replacements for conventional SRAM based memories even for the higher levels of the memory hierarchy. Many other new classes of emerging memory technologies such as transparent and plastic, three-dimensional(3-D), and quantum dot memory technologies have also gained tremendous popularity in recent years...En el campo de la informática, el término ‘memoria’ se refiere generalmente a dispositivos que son usados para almacenar información que posteriormente será usada en diversos dispositivos, desde computadoras personales (PC), móviles, dispositivos inteligentes, etc. La memoria principal del sistema se utiliza para almacenar los datos e instrucciones de los procesos que se encuentre en ejecución, por lo que se requiere que funcionen a alta velocidad (por ejemplo, DRAM). La memoria principal está implementada habitualmente mediante memorias semiconductoras direccionables, siendo DRAM y SRAM los principales exponentes. Por otro lado, la memoria auxiliar o secundaria proporciona almacenaje(para ficheros, por ejemplo); es más lenta pero ofrece una mayor capacidad. Ejemplos típicos de memoria secundaria son discos duros, memorias flash portables, CDs y DVDs. Debido a que estos dispositivos no necesitan estar conectados a la computadora de forma permanente, son muy utilizados para almacenar copias de seguridad. La memoria secundaria almacena una gran cantidad de datos aun coste menor por bit que la memoria principal, siendo habitualmente dos órdenes de magnitud más barata que la memoria primaria. Existen dos tipos de memorias de tipo semiconductor: volátiles y no volátiles. Ejemplos de memorias no volátiles son las memorias Flash (algunas veces usadas como memoria secundaria y otras veces como memoria principal) y memorias ROM/PROM/EPROM/EEPROM (usadas para firmware como programas de arranque). Ejemplos de memoria volátil son las memorias DRAM (RAM dinámica), actualmente la opción predominante a la hora de implementar la memoria principal, y las memorias SRAM (RAM estática) más rápida y costosa, utilizada para los diferentes niveles de cache. Las tecnologías de memorias no volátiles basadas en electrónica de silicio se remontan a la década de1990. Una variante de memoria de almacenaje por carga denominada como memoria Flash es mundialmente usada en productos electrónicos de consumo como telefonía móvil y reproductores de música mientras NAND Flash solid state disks(SSDs) están progresivamente desplazando a los dispositivos de disco duro como principal unidad de almacenamiento en computadoras portátiles, de escritorio e incluso en centros de datos. En la actualidad, hay varios factores que amenazan la actual predominancia de memorias semiconductoras basadas en cargas (capacitivas). Por un lado, se está alcanzando el límite de integración de las memorias Flash, lo que compromete su escalado en el medio plazo. Por otra parte, el fuerte incremento de las corrientes de fuga de los transistores de silicio CMOS actuales, supone un enorme desafío para la integración de memorias SRAM. Asimismo, estas memorias son cada vez más susceptibles a fallos de lectura/escritura en diseños de bajo consumo. Como resultado de estos problemas, que se agravan con cada nueva generación tecnológica, en los últimos años se han intensificado los esfuerzos para desarrollar nuevas tecnologías que reemplacen o al menos complementen a las actuales. Los transistores de efecto campo eléctrico ferroso (FeFET en sus siglas en inglés) se consideran una de las alternativas más prometedores para sustituir tanto a Flash (por su mayor densidad) como a DRAM (por su mayor velocidad), pero aún está en una fase muy inicial de su desarrollo. Hay otras tecnologías algo más maduras, en el ámbito de las memorias RAM resistivas, entre las que cabe destacar ReRAM (o RRAM), STT-RAM, Domain Wall Memory y Phase Change Memory (PRAM)...Depto. de Arquitectura de Computadores y AutomáticaFac. de InformáticaTRUEunpu

An FPGA implementation of an investigative many-core processor, Fynbos : in support of a Fortran autoparallelising software pipeline

Includes bibliographical references.In light of the power, memory, ILP, and utilisation walls facing the computing industry, this work examines the hypothetical many-core approach to finding greater compute performance and efficiency. In order to achieve greater efficiency in an environment in which Moore’s law continues but TDP has been capped, a means of deriving performance from dark and dim silicon is needed. The many-core hypothesis is one approach to exploiting these available transistors efficiently. As understood in this work, it involves trading in hardware control complexity for hundreds to thousands of parallel simple processing elements, and operating at a clock speed sufficiently low as to allow the efficiency gains of near threshold voltage operation. Performance is there- fore dependant on exploiting a new degree of fine-grained parallelism such as is currently only found in GPGPUs, but in a manner that is not as restrictive in application domain range. While removing the complex control hardware of traditional CPUs provides space for more arithmetic hardware, a basic level of control is still required. For a number of reasons this work chooses to replace this control largely with static scheduling. This pushes the burden of control primarily to the software and specifically the compiler, rather not to the programmer or to an application specific means of control simplification. An existing legacy tool chain capable of autoparallelising sequential Fortran code to the degree of parallelism necessary for many-core exists. This work implements a many-core architecture to match it. Prototyping the design on an FPGA, it is possible to examine the real world performance of the compiler-architecture system to a greater degree than simulation only would allow. Comparing theoretical peak performance and real performance in a case study application, the system is found to be more efficient than any other reviewed, but to also significantly under perform relative to current competing architectures. This failing is apportioned to taking the need for simple hardware too far, and an inability to implement static scheduling mitigating tactics due to lack of support for such in the compiler

Parallel and Distributed Computing

The 14 chapters presented in this book cover a wide variety of representative works ranging from hardware design to application development. Particularly, the topics that are addressed are programmable and reconfigurable devices and systems, dependability of GPUs (General Purpose Units), network topologies, cache coherence protocols, resource allocation, scheduling algorithms, peertopeer networks, largescale network simulation, and parallel routines and algorithms. In this way, the articles included in this book constitute an excellent reference for engineers and researchers who have particular interests in each of these topics in parallel and distributed computing