1,183 research outputs found

    A Comparative Study of Scheduling Techniques for Multimedia Applications on SIMD Pipelines

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    Parallel architectures are essential in order to take advantage of the parallelism inherent in streaming applications. One particular branch of these employ hardware SIMD pipelines. In this paper, we analyse several scheduling techniques, namely ad hoc overlapped execution, modulo scheduling and modulo scheduling with unrolling, all of which aim to efficiently utilize the special architecture design. Our investigation focuses on improving throughput while analysing other metrics that are important for streaming applications, such as register pressure, buffer sizes and code size. Through experiments conducted on several media benchmarks, we present and discuss trade-offs involved when selecting any one of these scheduling techniques.Comment: Presented at DATE Friday Workshop on Heterogeneous Architectures and Design Methods for Embedded Image Systems (HIS 2015) (arXiv:1502.07241

    Multiple voltage scheme with frequency variation for power minimization of pipelined circuits at high-level synthesis

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    High-Level Synthesis (HLS) is defined as a translation process from a behavioral description into structural description. The high-level synthesis process consists of three interdependent phases: scheduling, allocation and binDing The order of the three phases varies depending on the design flow. There are three important quality measures used to support design decision, namely size, performance and power consumption. Recently, with the increase in portability, the power consumption has become a very dominant factor in the design of circuits. The aim of low-power high-level synthesis is to schedule operations to minimize switching activity and select low power modules while satisfying timing constraints. This thesis presents a heuristic that helps minimize power consumption by operating the functional units at multiple voltages and varied clock frequencies. The algorithm presented here deals with pipelined operations where multiple instance of the same operation are carried out. The algorithm was implemented using C++, on LINUX platform

    A mathematical formulation of the loop pipelining problem

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    This paper presents a mathematical model for the loop pipelining problem that considers several parameters for optimization and supports any combination of resource and timing constraints. The unrolling degree of the loop is one of the variables explored by the model. By using Farey’s series, an optimal exploration of the unrolling degree is performed and optimal solutions not considered by other methods are obtained. Finding an optimal schedule that minimizes resource and register requirements is solved by using an Integer linear programming (ILP) model. A novel paradigm called branch and prune is proposed to eficiently converge towards the optimal schedule and prune the search tree for integer solutions, thus drastically reducing the running time. This is the first formulation that combines the unrolling degree of the loop with timing and resource constraints in a mathematical model that guarantees optimal solutions.Peer ReviewedPostprint (author's final draft

    The application of genetic algorithms to high-level synthesis

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    Predicate-aware, makespan-preserving software pipelining of scheduling tables

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    International audienceWe propose a software pipelining technique adapted to specific hard real-time scheduling problems. Our technique optimizes both computation throughput and execution cycle makespan, with makespan being prioritary. It also takes advantage of the predicated execution mechanisms of our embedded execution plat-form. To do so, it uses a reservation table formalism allowing the manipulation of the execution conditions of operations. Our reservation tables allow the double reservation of a resource at the same dates by two different operations, if the operations have exclusive execution conditions. Our analyses can determine when double reservation is possible even for operations belonging to different iterations

    Instruction fusion and vector processor virtualization for higher throughput simultaneous multithreaded processors

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    The utilization wall, caused by the breakdown of threshold voltage scaling, hinders performance gains for new generation microprocessors. To alleviate its impact, an instruction fusion technique is first proposed for multiscalar and many-core processors. With instruction fusion, similar copies of an instruction to be run on multiple pipelines or cores are merged into a single copy for simultaneous execution. Instruction fusion applied to vector code enables the processor to idle early pipeline stages and instruction caches at various times during program implementation with minimum performance degradation, while reducing the program size and the required instruction memory bandwidth. Instruction fusion is applied to a MIPS-based dual-core that resembles an ideal multiscalar of degree two. Benchmarking using an FPGA prototype shows a 6-11% reduction in dynamic power dissipation as well as a 17-45% decrease in code size with frequent performance improvements due to higher instruction cache hit rates. The second part of this dissertation deals with vector processors (VPs) which are commonly assigned exclusively to a single thread/core, and are not often performance and energy efficient due to mismatches with the vector needs of individual applications. An easy-to-implement VP virtualization technology is presented to improve the VP in terms of utilization and energy efficiency. The proposed VP virtualization technology, when applied, improves aggregate VP utilization by enabling simultaneous execution of multiple threads of similar or disparate vector lengths on a multithreaded VP. With a vector register file (VRF) virtualization technique invented to dynamically allocate physical vector registers to threads, the virtualization approach improves programmer productivity by providing at run time a distinct physical register name space to each competing thread, thus eliminating the need to solve register name conflicts statically. The virtualization technique is applied to a multithreaded VP prototyped on an FPGA; it supports VP sharing as well as power gating for better energy efficiency. A throughput-driven scheduler is proposed to optimize the virtualized VP’s utilization in dynamic environments where diverse threads are created randomly. Simulations of various low utilization benchmarks show that, with the proposed scheduler and power gating, the virtualized VP yields a larger than 3-fold speedup while the reduction in the total energy consumption approaches 40% compared to the same VP running in the single-threaded mode. The third part of this dissertation focuses on combining the two aforementioned technologies to create an improved VP prototype that is fully virtualized to support thread fusion and dynamic lane-based power-gating (PG). The VP is capable of dynamically triggering thread fusion according to the availability of similar threads in the task queue. Once thread fusion is triggered, every vector instruction issued to the virtualized VP is interpreted as two similar instructions working in two independent virtual spaces, thus doubling the vector instruction issue rate. Based on an accurate power model of the VP prototype, two different policies are proposed to dynamically choose the optimal number of active VP lanes. With the combined effort of VP lane-based PG and thread fusion, compared to a conventional VP without the two proposed capabilities, benchmarking shows that the new prototype yields up to 33.8% energy reduction in addition to 40% runtime improvement, or up to 62.7% reduction in the product of energy and runtime
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