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Data flow algorithms for processors with vector extensions: Handling actors with internal state

机译:具有矢量扩展的处理器的数据流算法:处理具有内部状态的参与者

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Full use of the parallel computation capabilities of present and expected CPUs and CPUs require use of vector extensions. Yet many actors in data flow systems for digital signal processing have internal state (or, equivalently, an edge that loops from the actor back to itself) that impose serial dependencies between actor invocations that make vectorizing across actor invocations impossible. Ideally, issues of inter-thread coordination required by serial data dependencies should be handled by code written by parallel programming experts that is separate from code specifying signal processing operations. The purpose of this paper is to present one approach for so doing in the case of actors that maintain state. We propose a methodology for using the parallel scan (also known as prefix sum) pattern to create algorithms for multiple simultaneous invocations of such an actor that results in vectorizable code. Two examples of applying this methodology are given: (1) infinite impulse response filters and (2) finite state machines. The correctness and performance of the resulting IIR filters are studied.
机译:充分利用当前和预期的CPU的并行计算功能以及CPU需要使用向量扩展。然而,用于数字信号处理的数据流系统中的许多参与者都具有内部状态(或等效地,从参与者循环回到自身的边缘),从而在参与者调用之间施加了串行依赖性,从而使得无法跨参与者调用进行矢量化。理想情况下,串行数据相关性所需的线程间协调问题应由并行编程专家编写的代码处理,该代码应与指定信号处理操作的代码分开。本文的目的是提出一种在行为者保持状态的情况下这样做的方法。我们提出了一种使用并行扫描(也称为前缀和)模式来创建算法的方法,该算法用于多次同时调用此类参与者,从而导致可矢量化的代码。给出了应用这种方法的两个例子:(1)无限冲激响应滤波器和(2)有限状态机。研究了所得IIR滤波器的正确性和性能。

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