Survey on Combinatorial Register Allocation and Instruction Scheduling

Register allocation (mapping variables to processor registers or memory) and instruction scheduling (reordering instructions to increase instruction-level parallelism) are essential tasks for generating efficient assembly code in a compiler. In the last three decades, combinatorial optimization has emerged as an alternative to traditional, heuristic algorithms for these two tasks. Combinatorial optimization approaches can deliver optimal solutions according to a model, can precisely capture trade-offs between conflicting decisions, and are more flexible at the expense of increased compilation time. This paper provides an exhaustive literature review and a classification of combinatorial optimization approaches to register allocation and instruction scheduling, with a focus on the techniques that are most applied in this context: integer programming, constraint programming, partitioned Boolean quadratic programming, and enumeration. Researchers in compilers and combinatorial optimization can benefit from identifying developments, trends, and challenges in the area; compiler practitioners may discern opportunities and grasp the potential benefit of applying combinatorial optimization

Cache-Aware Instruction SPM Allocation for Hard Real-Time Systems

To improve the execution time of a program, parts of its instructions can be allocated to a fast Scratchpad Memory (SPM) at compile time. This is a well-known technique which can be used to minimize the program's worst-case Execution Time (WCET). However, modern embedded systems often use cached main memories. An SPM allocation will inevitably lead to changes in the program's memory layout in main memory, resulting in either improved or degraded worst-case caching behavior. We tackle this issue by proposing a cache-aware SPM allocation algorithm based on integer-linear programming which accounts for changes in the worst-case cache miss behavior

WCET-aware prefetching of unlocked instruction caches: a technique for reconciling real-time guarantees and energy efficiency

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Automação e Sistemas, Florianópolis, 2015.A computação embarcada requer crescente vazão sob baixa potência. Ela requer um aumento de eficiência energética quando se executam programas de crescente complexidade. Muitos sistemas embarcados são também sistemas de tempo real, cuja correção temporal precisa ser garantida através de análise de escalonabilidade, a qual costuma assumir que o WCET de uma tarefa é conhecido em tempo de projeto. Como resultado da crescente complexidade do software, uma quantidade significativa de energia é gasta ao se prover instruções através da hierarquia de memória. Como a cache de instruções consome cerca de 40% da energia gasta em um processador embarcado e afeta a energia consumida em memória principal, ela se torna um relevante alvo para otimização. Entretanto, como ela afeta substancialmente o WCET, o comportamento da cache precisa ser restrito via  cache locking ou previsto via análise de WCET. Para obter eficiência energética sob restrições de tempo real, é preciso estender a consciência que o compilador tem da plataforma de hardware. Entretanto, compiladores para tempo real ignoram a energia, embora determinem rapidamente limites superiores para o WCET, enquanto compiladores para sistemas embarcados estimem com precisão a energia, mas gastem muito tempo em  profiling . Por isso, esta tese propõe um método unificado para estimar a energia gasta em memória, o qual é baseado em Interpretação Abstrata, exatamente o mesmo substrato matemático usado para a análise de WCET em caches. As estimativas mostram derivadas que são tão precisas quanto as obtidas via  profiling , mas são computadas 1000 vezes mais rápido, sendo apropriadas para induzir otimização de código através de melhoria iterativa. Como  cache locking troca eficiência energética por previsibilidade, esta tese propõe uma nova otimização de código, baseada em pré-carga por software, a qual reduz a taxa de faltas de caches de instruções e, provadamente, não aumenta o WCET. A otimização proposta é comparada com o estado-da-arte em  cache locking parcial para 37 programas do  Malardalen WCET benchmark para 36 configurações de cache e duas tecnologias distintas (2664 casos de uso). Em média, para obter uma melhoria de 68% no WCET,  cache locking parcial requer 8% mais energia. Por outro lado, a pré-carga por software diminui o consumo de energia em 11% enquanto melhora em 15% o WCET, reconciliando assim eficiência energética e garantias de tempo real.Abstract : Embedded computing requires increasing throughput at low power budgets. It asks for growing energy efficiency when executing programs of rising complexity. Many embedded systems are also real-time systems, whose temporal correctness is asserted through schedulability analysis, which often assumes that the WCET of each task is known at design-time. As a result of the growing software complexity, a significant amount of energy is spent in supplying instructions through the memory hierarchy. Since an instruction cache consumes around 40% of an embedded processor s energy and affects the energy spent in main memory, it becomes a relevant optimization target. However, since it largely impacts the WCET, cache behavior must be either constrained via cache locking or predicted by WCET analysis. To achieve energy efficiency under real-time constraints, a compiler must have extended awareness of the hardware platform. However, real-time compilers ignore energy, although they quickly determine bounds for WCET, whereas embedded compilers accurately estimate energy but require time-consuming profiling. That is why this thesis proposes a unifying method to estimate memory energy consumption that is based on Abstract Interpretation, the very same mathematical framework employed for the WCET analysis of caches. The estimates exhibit derivatives that are as accurate as those obtained by profiling, but are computed 1000 times faster, being suitable for driving code optimization through iterative improvement. Since cache locking gives up energy efficiency for predictability, this thesis proposes a novel code optimization, based on software prefetching, which reduces miss rate of unlocked instruction caches and, provenly, does not increase the WCET. The proposed optimization is compared with a state-of-the-art partial cache locking technique for the 37 programs of the Malardalen WCET benchmarks under 36 cache configurations and two distinct target technologies (2664 use cases). On average, to achieve an improvement of 68% in the WCET, partial cache locking required 8% more energy. On the other hand, software prefetching decreased the energy consumption by 11% while leading to an improvement of 15% in the WCET, thereby reconciling energy efficiency and real-time guarantees

Fast, predictable and low energy memory references through architecture-aware compilation

The design of future high-performance embedded systems is hampered by two problems: First, the required hardware needs more energy than is available from batteries. Second, current cache-based approaches for bridging the increasing speed gap between processors and memories cannot guarantee predictable real-time behavior. A contribution to solving both problems is made in this paper which describes a comprehensive set of algorithms that can be applied at design time in order to maximally exploit scratch pad memories (SPMs). We show that both the energy consumption as well as the computed worst case execution time (WCET) can be reduced by up to to 80% and 48%, respectively, by establishing a strong link between the memory architecture and the compiler

WCET-Aware Scratchpad Memory Management for Hard Real-Time Systems

abstract: Cyber-physical systems and hard real-time systems have strict timing constraints that specify deadlines until which tasks must finish their execution. Missing a deadline can cause unexpected outcome or endanger human lives in safety-critical applications, such as automotive or aeronautical systems. It is, therefore, of utmost importance to obtain and optimize a safe upper bound of each task’s execution time or the worst-case execution time (WCET), to guarantee the absence of any missed deadline. Unfortunately, conventional microarchitectural components, such as caches and branch predictors, are only optimized for average-case performance and often make WCET analysis complicated and pessimistic. Caches especially have a large impact on the worst-case performance due to expensive off- chip memory accesses involved in cache miss handling. In this regard, software-controlled scratchpad memories (SPMs) have become a promising alternative to caches. An SPM is a raw SRAM, controlled only by executing data movement instructions explicitly at runtime, and such explicit control facilitates static analyses to obtain safe and tight upper bounds of WCETs. SPM management techniques, used in compilers targeting an SPM-based processor, determine how to use a given SPM space by deciding where to insert data movement instructions and what operations to perform at those program locations. This dissertation presents several management techniques for program code and stack data, which aim to optimize the WCETs of a given program. The proposed code management techniques include optimal allocation algorithms and a polynomial-time heuristic for allocating functions to the SPM space, with or without the use of abstraction of SPM regions, and a heuristic for splitting functions into smaller partitions. The proposed stack data management technique, on the other hand, finds an optimal set of program locations to evict and restore stack frames to avoid stack overflows, when the call stack resides in a size-limited SPM. In the evaluation, the WCETs of various benchmarks including real-world automotive applications are statically calculated for SPMs and caches in several different memory configurations.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Worst-Case Execution Time Analysis of Predicated Architectures

The time-predictable design of computer architectures for the use in (hard) real-time systems is becoming more and more important, due to the increasing complexity of modern computer architectures. The design of predictable processor pipelines recently received considerable attention. The goal here is to find a trade-off between predictability and computing power. Branches and jumps are particularly problematic for high-performance processors. For one, branches are executed late in the pipeline. This either leads to high branch penalties (flushing) or complex software/hardware techniques (branch predictors). Another side-effect of branches is that they make it difficult to exploit instruction-level parallelism due to control dependencies. Predicated computer architectures allow to attach a predicate to the instructions in a program. An instruction is then only executed when the predicate evaluates to true and otherwise behaves like a simple nop instruction. Predicates can thus be used to convert control dependencies into data dependencies, which helps to address both of the aforementioned problems. A downside of predicated instructions is the precise worst-case execution time (WCET) analysis of programs making use of them. Predicated memory accesses, for instance, may or may not have an impact on the processor\u27s cache and thus need to be considered by the cache analysis. Predication potentially has an impact on all analysis phases of a WCET analysis tool. We thus explore a preprocessing step that explicitly unfolds the control-flow graph, which allows us to apply standard analyses that are themselves not aware of predication

Architectural support for real-time task scheduling in SMT processors

In Simultaneous Multithreaded (SMT) architectures most hardware resources are shared between threads. This provides a good cost/performance trade-off which renders these architectures suitable for use in embedded systems. However, since threads share many resources, like caches, they also interfere with each other. As a result, execution times of applications become highly unpredictable and highly dependent on the context in which an application is executed. Obviously, this poses problems if an SMT is to be used in a (soft) real time system. In this paper, we propose two novel hardware mechanisms that can be used to reduce this performance variability. In contrast to previous approaches, our proposed mechanisms do not need any information beyond the information already known by traditional job schedulers. Neither do they require extensive profiling of workloads to determine optimal schedules. Our mechanisms are based on dynamic resource partitioning. The OS level job scheduler needs to be slightly adapted in order to provide the hardware resource allocator some information on how this resource partitioning needs to be done. We show that our mechanisms provide high stability for SMT architectures to be used in real time systems: the real time benchmarks we used meet their deadlines in more than 98% of the cases considered while the other thread in the workload still achieves high throughput.Postprint (published version

An Instruction Scratchpad Memory Allocation for the Precision Timed Architecture

This work presents a static instruction allocation scheme for the precision timed architecture’s (PRET) scratchpad memory. Since PRET provides timing instructions to control the temporal execution of programs, the objective of the allocation scheme is to ensure that the explicitly specified temporal requirements are met. Furthermore, this allocation incorporates instructions from multiple hardware threads of the PRET architecture. We formulate the allocation as an integer-linear programming problem, and we implement a tool that takes binaries, constructs a control-flow graph, performs the allocation, rewrites the binary with the new allocation, and generates an output binary for the PRET architecture. We carry out experiments on a modified version of the Malardalen benchmarks to illustrate that commonly known ACET and WCET based approaches cannot be directly applied to meet explicit timing requirements. We also show the advantage of performing the allocation across multiple threads. We present a real time benchmark controlling an Unmanned Air Vehicle as the case study