Research and Implementation of Computational Storage System for High-Energy Physics

In high-energy physics experiments, data processing typically involves a compute-storage separated computing model. During the computation process, data must be transferred between the computing and storage nodes. The continuous growth in experimental data and data analysis demands has led to data transfer bottlenecks, reducing the overall processing efficiency of these systems. This paper proposes a computational storage system for high-energy physics. First, the storage software EOS is extended. Computational storage plugins are introduced by building on the original architecture. After parsing user commands, the storage server executes local computations based on the file I/O, thereby reducing data movement, alleviating network pressure, and enhancing data processing efficiency. Second, a computational storage server based on a Central Processing Unit-Field Programmable Gate Array (CPU-FPGA) heterogeneous computing architecture is constructed. Considering the lower computational complexity of I/O-intensive tasks, tasks suitable for parallel computing are offloaded to the FPGA via the PCIe bus, thereby extending the computational capabilities of the storage server. Experimental evaluations show that the computational storage system eliminates queuing time and network latency, thereby shortening the overall execution time of computational tasks. Moreover, leveraging FPGA-based hardware acceleration effectively compensates for the weak computing performance of CPUs in storage servers, thereby enhancing the algorithmic versatility of computational storage devices. In tests based on decoding by LHAASO, the computational storage system achieves a speedup of approximately sixfold.