20,302 research outputs found

    Survey on Combinatorial Register Allocation and Instruction Scheduling

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    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

    Modulo scheduling with integrated register spilling for clustered VLIW architectures

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    Clustering is a technique to decentralize the design of future wide issue VLIW cores and enable them to meet the technology constraints in terms of cycle time, area and power dissipation. In a clustered design, registers and functional units are grouped in clusters so that new instructions are needed to move data between them. New aggressive instruction scheduling techniques are required to minimize the negative effect of resource clustering and delays in moving data around. In this paper we present a novel software pipelining technique that performs instruction scheduling with reduced register requirements, register allocation, register spilling and inter-cluster communication in a single step. The algorithm uses limited backtracking to reconsider previously taken decisions. This backtracking provides the algorithm with additional possibilities for obtaining high throughput schedules with low spill code requirements for clustered architectures. We show that the proposed approach outperforms previously proposed techniques and that it is very scalable independently of the number of clusters, the number of communication buses and communication latency. The paper also includes an exploration of some parameters in the design of future clustered VLIW cores.Peer ReviewedPostprint (published version

    Hierarchical clustered register file organization for VLIW processors

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    Technology projections indicate that wire delays will become one of the biggest constraints in future microprocessor designs. To avoid long wire delays and therefore long cycle times, processor cores must be partitioned into components so that most of the communication is done locally. In this paper, we propose a novel register file organization for VLIW cores that combines clustering with a hierarchical register file organization. Functional units are organized in clusters, each one with a local first level register file. The local register files are connected to a global second level register file, which provides access to memory. All intercluster communications are done through the second level register file. This paper also proposes MIRS-HC, a novel modulo scheduling technique that simultaneously performs instruction scheduling, cluster selection, inserts communication operations, performs register allocation and spill insertion for the proposed organization. The results show that although more cycles are required to execute applications, the execution time is reduced due to a shorter cycle time. In addition, the combination of clustering and hierarchy provides a larger design exploration space that trades-off performance and technology requirements.Peer ReviewedPostprint (published version

    Optimizing construction of scheduled data flow graph for on-line testability

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    The objective of this work is to develop a new methodology for behavioural synthesis using a flow of synthesis, better suited to the scheduling of independent calculations and non-concurrent online testing. The traditional behavioural synthesis process can be defined as the compilation of an algorithmic specification into an architecture composed of a data path and a controller. This stream of synthesis generally involves scheduling, resource allocation, generation of the data path and controller synthesis. Experiments showed that optimization started at the high level synthesis improves the performance of the result, yet the current tools do not offer synthesis optimizations that from the RTL level. This justifies the development of an optimization methodology which takes effect from the behavioural specification and accompanying the synthesis process in its various stages. In this paper we propose the use of algebraic properties (commutativity, associativity and distributivity) to transform readable mathematical formulas of algorithmic specifications into mathematical formulas evaluated efficiently. This will effectively reduce the execution time of scheduling calculations and increase the possibilities of testability

    Scratchpad Sharing in GPUs

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    GPGPU applications exploit on-chip scratchpad memory available in the Graphics Processing Units (GPUs) to improve performance. The amount of thread level parallelism present in the GPU is limited by the number of resident threads, which in turn depends on the availability of scratchpad memory in its streaming multiprocessor (SM). Since the scratchpad memory is allocated at thread block granularity, part of the memory may remain unutilized. In this paper, we propose architectural and compiler optimizations to improve the scratchpad utilization. Our approach, Scratchpad Sharing, addresses scratchpad under-utilization by launching additional thread blocks in each SM. These thread blocks use unutilized scratchpad and also share scratchpad with other resident blocks. To improve the performance of scratchpad sharing, we propose Owner Warp First (OWF) scheduling that schedules warps from the additional thread blocks effectively. The performance of this approach, however, is limited by the availability of the shared part of scratchpad. We propose compiler optimizations to improve the availability of shared scratchpad. We describe a scratchpad allocation scheme that helps in allocating scratchpad variables such that shared scratchpad is accessed for short duration. We introduce a new instruction, relssp, that when executed, releases the shared scratchpad. Finally, we describe an analysis for optimal placement of relssp instructions such that shared scratchpad is released as early as possible. We implemented the hardware changes using the GPGPU-Sim simulator and implemented the compiler optimizations in Ocelot framework. We evaluated the effectiveness of our approach on 19 kernels from 3 benchmarks suites: CUDA-SDK, GPGPU-Sim, and Rodinia. The kernels that underutilize scratchpad memory show an average improvement of 19% and maximum improvement of 92.17% compared to the baseline approach

    Coarse-grained reconfigurable array architectures

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    Coarse-Grained Reconfigurable Array (CGRA) architectures accelerate the same inner loops that benefit from the high ILP support in VLIW architectures. By executing non-loop code on other cores, however, CGRAs can focus on such loops to execute them more efficiently. This chapter discusses the basic principles of CGRAs, and the wide range of design options available to a CGRA designer, covering a large number of existing CGRA designs. The impact of different options on flexibility, performance, and power-efficiency is discussed, as well as the need for compiler support. The ADRES CGRA design template is studied in more detail as a use case to illustrate the need for design space exploration, for compiler support and for the manual fine-tuning of source code
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