This study focuses on the acceleration of cryptographic pairing operations on field-programmable gate arrays (FPGAs) for server-side applications. Previous studies on FPGA pairing implementations focused on area efficiency for embedded devices, trying to achieve maximum performance with minimal circuit resources. However, their architectures are likely to be inefficient for server-side applications, where the primary interest is maximum performance when FPGA resources are finished. Their architectures are inefficient for two reasons: low utilization of the digital signal processor (DSP) and low operation frequency. In this study, we propose a high-throughput pairing processor architecture for server-side FPGAs, taking full advantage of DSPs. First, we propose a loop-unrolled modular multiplication algorithm that is suitable for a server-side FPGA. The algorithm shows the highest throughput and area efficiency compared to algorithms from previous studies. Second, we design a pairing processor architecture that embeds the proposed modular multiplier, thus, maintaining its high throughput by supporting redundant adders and interleaved executions. We evaluate BN254 and BLS12_381 pairings on the proposed processor architecture and the evaluation results show that it achieves good throughput that is approximately two and five times faster than that from previous studies, respectively.

We report a Vlasov simulation of cosmic relic neutrinos combined with N-body simulation of cold dark matter in the context of large-scale structure formation in the Universe performed on Fugaku supercomputer. Gravitational dynamics of the neutrinos is followed, for the first time, by directly integrating the Vlasov equation in a six-dimensional phase space. Our largest simulation combines the Vlasov simulation on 400 trillion grids and 330 billion-body calculations in a self-consistent manner, and reproduces accurately the nonlinear dynamics of neutrinos in the Universe. The novel high-order Vlasov solver is optimized by combining an array of state-of-the-art numerical schemes and fully utilizing the SIMD instructions on the A64FX processors. Time-To-Solution of our simulation is an order of magnitude shorter than the largest N-body simulations. The performance scales excellently with up to 147,456 nodes (7 million CPU cores) on Fugaku; the weak and strong scaling efficiencies are 82% - 96% and 82% - 93%, respectively.

Recently, network management becomes therefore more important to save a safe and secure ICT infrastructure. Since it is difficult to take appropriate actions against rapid, complicated, and diversed variation of behaviors in networking and service systems, conventional network management heavily relies on highly expertised operators. Automation of the management of ICT infrastructure is now a big challenging for future networks due to shortage of experts in network operations and management. In this paper, we propose a new framework for automating operations and management of ICT infrastructure, by combination of both networking/system incidents and records of operations. Our framework mainly focuses on the integration of various types of log data (e.g., alerts, flow analysis, access logs, command execution logs, etc.). As a proof of concept (PoC), we demonstrate an implementation of our framework by using honeypots and ssh-based agents.