Asynchronized Jacobi Solver on Heterogeneous Mobile Devices

Many vision and graphics applications involve the efficient solving of various linear systems, which has been a popular topic for decades. With mobile devices arising and becoming popularized, designing a high-performance solver tailored for them, to ensure the smooth migration of various applications from PC to mobile devices, has become urgent. However, the unique features of mobile devices present new challenges. Mainstream mobile devices are equipped with so-called heterogeneous multiprocessor systems-on-chips (MPSoCs), which consist of processors with different architectures and performances. Designing algorithms to push the limits of of MPSoCs is attractive yet difficult. Different cores are suitable for different tasks. Further, data sharing among different cores can easily neutralize performance gains. Fortunately, the comparable performance of CPUs and GPUs on MPSoCs make the heterogeneous systems promising, compared to their counterparts on PCs. This paper is devoted to a high-performance mobile linear solver for a sparse system with a tailored asynchronous algorithm, to fully exploit the computing power of heterogeneous processors on mobile devices while alleviating the data-sharing overhead. Comprehensive evaluations are performed, with in-depth discussion to shed light on the future design of other numerical solvers.