Compiling C/C++ SIMD Extensions for Function and Loop Vectorizaion on Multicore-SIMD Processors

Abstract

SIMD vectorization has received significant attention in the past decade as an important method to accelerate scientific applications, media and embedded applications on SIMD architectures such as Intel ® SSE, AVX, and IBM * AltiVec. However, most of the focus has been directed at loops, effectively executing their iterations on multiple SIMD lanes concurrently relying upon program hints and compiler analysis. This paper presents a set of new C/C++ high-level vector extensions for SIMD programming, and the Intel® C++ product compiler that is extended to translate these vector extensions and produce optimized SIMD instruction sequences of vectorized functions and loops. For a function, our main idea is to vectorize the entire function for callers instead of just vectorizing loops (if any) inside the function. It poses the challenge of dealing with complicated control-flow in the function body, and matching caller and callee for SIMD vector calls while vectorizing caller functions (or loops) and callee functions. Our compilation methods for automatically compiling vector extensions are described. We present performance results of several non-trivial visual computing, computational, and simulation workloads, utilizing SIMD units through the vector extensions on Intel® Multicore 128-bit SIMD processors, and we show that significant SIMD speedups (3.07x to 4.69x) are achieved over the serial execution.

Single-Instruction Multiple-Data Execution

“…In some cases, loop transformations may eliminate control flow differences [Hanxleden and Kennedy, 1992]. It's also possible for control flow to be consistent across data elements, but for there to be challenges in determining this, such as function calls; sophisticated analysis may be required in these situations [Tian et al, 2012]. e compiler may instead use some conditional SIMD operations to convert control flow into data flow, enabling SIMD execution at the cost of some efficiency [Bik et al, 2002].…”

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“…Details about the specific compiler techniques are available in Tian et al 26 The compiler directives we add to the code and command line are the following:…”

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“…We focus on aggressive inter-iteration parallelism, consistent with presence of wide SIMD lanes. Tian et al [26] provided an extension to the current directive vectorization methods to support function call. ISPC [22] provides a compiler based solution supporting function calls, SOA data structure, and control flow.…”