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Efficient multimedia coprocessor with enhanced SIMD engines for exploiting ILP and DLP
Affiliation:1. Department of Mathematics and Center for Computation and Technology, Louisiana State University, Baton Rouge, LA 70803, USA;2. Pacific Northwest National Laboratory, Richland, WA 99352, USA;1. Jiangsu Key Laboratory for Optoelectronic Detection of Atmosphere and Ocean, School of Physics and Optoelectronic Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China;2. Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET), Nanjing University of Information Science & Technology, Nanjing 210044, China;1. Integrated Systems Laboratory (LSI), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland;2. Dipartimento di Energia Elettrica e Informazione (DEI), University of Bologna (UNIBO), Bologna 40136, Italy;3. iNoCs SaRL, Lausanne, Switzerland;1. School of Electrical and Computer Engineering, College of Engineering, University of Tehran, P.O. Box 14395-515, Tehran, Iran;2. School of Computer Science, Institute for Research in Fundamental Sciences (IPM), P.O. Box 19395-5746, Tehran, Iran
Abstract:Multimedia applications have become increasingly important in daily computing. These applications are composed of heterogeneous regions of code mixed with data-level parallelism (DLP) and instruction-level parallelism (ILP). A standard solution for a multimedia coprocessor resembles of single-instruction multiple-data (SIMD) engines into architectures exploiting ILP at compile time, such as very long instruction word (VLIW) and transport triggered architecture (TTA). However, the ILP regions fail to scale with the increased vector length to achieve high performance in the DLP regions. Furthermore, the register-to-register nature of SIMD instructions causes current SIMD engines to have limitations in handling memory alignment, data reorganization, and control flow. Many supporting instructions such as data permutations, address generations, and loop branches, are required to aid in the execution of the real SIMD computation instructions. To mitigate these problems, we propose optimized SIMD engines that have the capabilities for combining VLIW or TTA processing with a unified scalar and long vector computations as well as efficient SIMD hardware for real computation. Our new architecture is based on TTA and is called multimedia coprocessor (MCP). This architecture includes following features: (1) a simple coprocessor structure with 8-way TTA, (2) cost-effective SIMD hardware capable of performing floating-point operations, (3) long vector capabilities built upon existing SIMD hardware and a single register file and processor data path for both scalar operands and vector elements, and (4) an optimized SIMD architecture that addresses the SIMD limitations. Our experimental evaluations show that MCP can outperform conventional SIMD techniques by an average of 39% and 12% in performance for multimedia kernels and applications, respectively.
Keywords:Scalar  Vector  SIMD  VLIW  TTA  Multimedia coprocessor
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