Gene data calculation and interpretation-based heterogeneous platform

Abstract

The invention discloses a gene data calculation and interpretation-based heterogeneous platform. The heterogeneous platform comprises a heterogeneous processor unit, an interconnection bus module, a memory, a gene calculation and interpretation data instruction input unit and a gene calculation and interpretation result output unit, wherein the heterogeneous processor unit is connected with the memory, the gene calculation and interpretation data instruction input unit and the gene calculation and interpretation result output unit through the interconnection bus module; the heterogeneous processor unit comprises a CPU, a GPU, a DSP and an FPGA; the CPU forms a control engine; the CPU, the GPU and the FPGA form a calculation engine; and the CPU, the GPU and the DSP form an interpretation engine. The heterogeneous platform can provide hardware support for improving the timeliness and accuracy of gene data calculation and improving the accuracy and readability of gene data interpretation, and has the advantages of high gene data calculation and interpretation efficiency, low manufacturing cost and low calculation and interpretation energy consumption.

Description

technical field [0001] The invention relates to gene sequencing technology, in particular to a heterogeneous platform oriented to calculation and interpretation of gene data. Background technique [0002] In recent years, with the widespread application of Next Generation Sequencing technology (Next Generation Sequence, hereinafter referred to as NGS), the cost of gene sequencing has dropped rapidly, and gene technology has begun to be widely used. NGS includes two steps: genetic data calculation and genetic data interpretation. Genetic data calculation refers to the preprocessing of the original gene sequencing data, such as de-falsification and de-duplication, so that it can be used in the interpretation of genetic data. Genetic data interpretation refers to the analysis of genetic data. Analyze, reveal and explain the scientific meaning of genetic data processed by calculation in the fields of biology, medicine, health care and so on. [0003] There are two bottlenecks i...

AI Technical Summary

Problems solved by technology

However, the disadvantages of this system are: on the one hand, its high cost in storage, power consumption, technical support and maintenance; Meet the needs of the above challenges; more importantly, the increase in raw genetic data generated by sequencing has far exceeded Moore's Law, so this method has been lacking in sustainability

The disadvantage is: to achieve the same function, FPGA is generally slower than ASIC (Application Specific Integrated Circuit, ASIC), and the circuit area is larger than ASIC

However, there are two problems with the current GPU: First, due to the hardware structural characteristics of the GPU, many parallel algorithms cannot be effectively executed on the GPU; second, the GPU will generate a lot of heat during operation, and the energy consumption is high

To sum up, the above four computing devices have their own characteristics and limitations.

Images