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Heterogeneous multicore processor systems, as one of the highlights of multicore processor systems, are widely loved by people for their high efficiency and low cost, and they have also become the most commonly used processor systems in embedded systems. In the process of research on heterogeneous multicore processor systems, system task scheduling is particularly important. A good task scheduling algorithm can give full play to system performance. In this paper, the intelligent approximation algorithm is applied to the task scheduling problem of heterogeneous multicore processor system, and the heterogeneous multicore processor system is obtained as a highlight in the multicore processor system. Relying on the characteristics of high efficiency and low cost, it is widely loved by people, and at the same time, it has become the most commonly used processor system in embedded systems. In the process of research on heterogeneous multicore processor systems, the system task scheduling problem is particularly important. A good task scheduling algorithm can give full play to system performance. Some commonly used heuristic task scheduling algorithms are insufficient in solving such problems. This paper combines the granularity-based wavefront parallel decoding algorithm and the fast fusion loop filter algorithm to apply pipeline parallel technology between pixels. Decoding reconstruction module and fast loop filter module realize the fusion of multilevel parallel decoding. Based on the multicore platform, a dynamic multiparallel scheduling algorithm is designed to realize two-way video real-time parallel high-speed decoding, which improves the core resource utilization rate and decoding execution efficiency of the multicore processing platform. This paper also designs an indicator collector, a read-write hit collector, and a cache block priority determiner to implement a dynamic generation strategy with low hardware overhead. Multimodal teaching has certain feasibility and effectiveness and can have a positive impact on the English reading motivation and English reading comprehension ability of university students. Multimodal teaching improves students’ English reading comprehension ability, deepens students’ understanding and memory of words, and broadens the scope of knowledge, which has a significant promoting effect. The research results show that multimodality can be applied to college English teaching, and it can achieve better results than traditional teaching methods. By comparing the test results before and after the test, there are obvious differences between the experimental class and the control class. Whether it is the paired sample T-test of the experimental class or the independent sample T-test of two teaching methods in two classes, it proves that the scores under the multimodal English teaching mode are higher than the traditional teaching mode. Multimodal classrooms provide students with many opportunities to participate in classroom activities and form a competitive learning atmosphere. This competitive learning atmosphere has become a driving force to promote student learning. Multimodal teaching methods help to cultivate students’ independent and cooperative learning. In a multimodal classroom, many activities require cooperation and discussion among students. When they encounter difficulties, they can help each other, discuss with each other, and cooperate to complete tasks. Therefore, the multimodal teaching method will stimulate students’ interest in learning, give full play to students’ initiative, and improve students’ English ability.

Construction of Dynamic Multiparallel Foreign Language Teaching Model Based on Multicore Processor