The equidistortion principle[1] has recently been proposed as a basic principle for design of an optimal vector quantization (VQ) codebook. The equidistortion principle adjusts all codebook vectors such that they have the same contribution to quantization error. This paper introduces a novel VQ codebook design algorithm based on the equidistortion principle. The proposed algorithm is a variant of the law-of-the-jungle algorithm (LOJ), which duplicates useful codebook vectors and removes useless vectors. Due to the LOJ mechanism, the proposed algorithm can establish the equidistortion condition without wasting learning steps. This is significantly effective in preventing performance degradation caused when initial states of codebook vectors are improper to find an optimal codebook. Therefore, even in the case of improper initialization, the proposed algorithm can achieve minimization of quantization error based on the equidistortion principle. Performance of the proposed algorithm is discussed through experimental results.

A data-parallel processing approach is promising for real-time volume rendering because of the massive parallelism in volume rendering. In data-parallel volume rendering, local results processing elements(PEs) generate from allocated subvolumes are integrated to form a final image. Generally, the integration causes an overhead unavoidable in data-parallel volume rendering due to communications among PEs. This paper proposes a data-parallel shear-warp volume rendering algorithm combined with an adaptive volume subdivision method to reduce the communication overhead and improve processing efficiency. We implement the parallel algorithm on a message-passing multiprocessor system for performance evaluation. The experimental results show that the adaptive volume subdivision method can reduce the overhead and achieve higher efficiency compared with a conventional slab subdivision method.

Since the hardware resource of a single FPGA is limited, one idea to scale the performance of FPGA-based HPC applications is to expand the design space with multiple FPGAs. This paper presents a scalable architecture of a deeply pipelined stream computing platform, where available parallelism and inter-FPGA link characteristics are investigated to achieve a scaled performance. For a practical exploration of this vast design space, a performance model is presented and verified with the evaluation of a tsunami simulation application implemented on Intel Arria 10 FPGAs. Finally, scalability analysis is performed, where speedup is achieved when increasing the computing pipeline over multiple FPGAs while maintaining the problem size of computation. Performance is scaled with multiple FPGAs; however, performance degradation occurs with insufficient available bandwidth and large pipeline overhead brought by inadequate data stream size. Tsunami simulation results show that the highest scaled performance for 8 cascaded Arria 10 FPGAs is achieved with a single pipeline of 5 stream processing elements (SPEs), which obtained a scaled performance of 2.5 TFlops and a parallel efficiency of 98%, indicating the strong scalability of the multi-FPGA stream computing platform.

Location information is essential to varieties of applications. It is one of the most important context to be detected by wireless distributed sensors, which is a key technology in Internet-of-Things. Fingerprint-based methods, which compare location unique fingerprints collected beforehand with the fingerprint measured from the target, have attracted much attention recently in both of academia and industry. They have been successfully used for many location-based applications. From the viewpoint of practical applications, in this paper, four different typical approaches of fingerprint-based radio emitter localization system are introduced with four different representative applications: localization of LTE smart phone used for anti-cheating in exams, indoor localization of Wi-Fi terminals, localized light control in BEMS using location information of occupants, and illegal radio localization in outdoor environments. Based on the different practical application scenarios, different solutions, which are designed to enhance the localization performance, are discussed in detail. To the best of the authors' knowledge, this is the first paper to give a guideline for readers about fingerprint-based localization system in terms of fingerprint selection, hardware architecture design and algorithm enhancement.