Quantifying Intrinsic Parallelism Using Linear Algebra for Algorithm/Architecture Coexploration


Degree of parallelism (DoP) is an essential complexity metric that characterizes the number of independent operation sets (IOSs) that can be concurrently executed within an algorithm. This paper presents a generic framework to identify IOSs and to quantify the DoP based on rank theorem in linear algebra. This framework is applied to extract algorithmic parallelisms at various granularities, namely, multigrain parallelism. Our parallelism is intrinsic and platform independent and can provide insights into architectural information, thus facilitating mapping onto generic platforms and early back annotation for modifying algorithms. It plays a significant role in the concurrent optimization of both algorithms and architectures, referred to as Algorithm/Architecture Coexploration (AAC), by trading off between the DoP and the number of operations (NoO). This paper reports three case studies for AAC. The case study on an IDCT reveals that our framework accurately quantifies the parallelism for mapping the algorithm onto generic platforms, including FPGA and multicore systems. The IDCT parallelized by our technique surpasses a conventional spectral parallelization. By exploiting fine-grain parallelism, this paper presents a better porting of a discrete wavelet transform (DWT) onto single instruction multiple data (SIMD) machines compared with a commercial compiler. A high-quality deinterlacer is implemented on a low-cost multicore platform for real-time high-definition applications by analyzing the multigrain parallelism. These case studies reveal the effectiveness of our parallel analysis framework which is applicable to generic systems. Compared with traditional graph traversal techniques, our linear algebraic approach impressively features low complexity and is practical for complicated algorithms.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE :Quantifying Spatial–Temporal Pattern of Urban Heat Island in Beijing: An Improved Assessment Using Land Surface Temperature (LST) Time Series Observations From LANDSAT, MODIS, and Chinese New Satellite GaoFen-1ABSTRACT:The
PROJECT TITLE :Quantifying edge and peripheral recombination losses in industrial silicon solar cellsABSTRACT:A finite-element model is built to represent a silicon solar cell as an enormous network of diodes with completely different
PROJECT TITLE :Quantifying Tidal Mud Flat Elevations From Fixed-Platform Long-Wave Infrared ImageryABSTRACT:A procedure for estimating tidal mud flat topography from fastened-platform, long-wave infrared imagery is presented.
PROJECT TITLE :Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless NetworksABSTRACT:Conventional cellular wireless networks were designed with the purpose of providing high throughput for the user and high
PROJECT TITLE :Quantifying the Transmit Diversity Order of Euclidean Distance Based Antenna Selection in Spatial ModulationABSTRACT:During this letter, we tend to quantify the transmit diversity order of the SM system operating

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry