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Method for achieving large-scale high-performance Linpack testing benchmark for GPDSP

A high-performance, large-scale technology, used in the detection of faulty computer hardware, complex mathematical operations, etc., to solve problems such as the inability to obtain GPDSP performance test results

Active Publication Date: 2015-05-13
NAT UNIV OF DEFENSE TECH
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Problems solved by technology

Since GPDSP is a heterogeneous multi-core processor including CPU core and DSP core, including register file, on-chip vector array memory, on-chip shared memory array, off-chip DDR memory and other multi-level storage architectures, simply transplant HPL or use traditional The Linpack test benchmark implemented by the method cannot obtain the best performance test results of GPDSP

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  • Method for achieving large-scale high-performance Linpack testing benchmark for GPDSP
  • Method for achieving large-scale high-performance Linpack testing benchmark for GPDSP
  • Method for achieving large-scale high-performance Linpack testing benchmark for GPDSP

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Embodiment Construction

[0046] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0047] The method for realizing the GPDSP-oriented large-scale high-performance Linpack test benchmark of the present invention is to solve dense linear equations in a block-by-block manner. In the solving process, small serial tasks and small matrix inversion and triangular equation solving tasks that are not suitable for DSP core vector processing array vectorization calculations, such tasks have relatively small calculations, and the calculation data storage mode is not suitable for efficient vectors Processing is handled by the CPU core. For regular calculation tasks (such as matrix and matrix multiplication), it is suitable for DSP core vector processing array vectorization calculation. The calculation amount of this type of task occupies the vast majority of Linpack calculation, and the DSP core is responsible for it. The calcu...

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Abstract

The invention discloses a method for achieving a large-scale high-performance Linpack testing benchmark for a GPDSP. The method comprises the steps that a dense linear system of equations is solved in a partitioning mode, wherein a CPU core in the GPDSP is in charge of small serial tasks, small matrix inversion and trigonometric equation solving tasks; a DSP core in the GPDSP is in charge of regular computation tasks. The method has the advantages that the principle is simple, operation is convenient, the powerful vector parallel computation capacity of a vector processing array and the high-bandwidth vector data loading capacity of the DSP core in the GPDSP can be fully utilized, and computation of the large-scale Linpack testing benchmark is achieved through the CPU core and the DSP core cooperatively and efficiently.

Description

technical field [0001] The present invention mainly relates to a general-purpose digital signal processor (General-Purpose Digital Signal Processor, GPDSP for short), in particular to a method for realizing a large-scale high-performance Linpack test benchmark suitable for GPDSP. Background technique [0002] The Linpack test benchmark is the most widely used performance test benchmark in high-performance computing, and it is the most important test benchmark of TOP500. The Linpack benchmark tests and evaluates the floating-point performance of high-performance computer systems by solving dense linear algebraic equations. The Linpack test standard includes three tests with different data scales: 100×100, 1000×1000 and n×n, among which the test benchmark program used in the first two tests can be obtained from the website (for example: http: / / www.netlib. org / benchmark / ), after compiling and running the program, the program will give the performance of the corresponding machi...

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Application Information

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IPC IPC(8): G06F11/22G06F17/12
Inventor 刘仲陈书明郭阳陈海燕万江华陈磊田希孙永节彭元喜扈啸王耀华马胜陈虎张军阳鲁庆男
Owner NAT UNIV OF DEFENSE TECH