Fully homomorphic encryption (FHE) enables secret computations. Users can perform computation using data encrypted with FHE without decryption. Uploading private data without encryption to a public cloud has the risk of data leakage, which makes many users hesitant to utilize a public cloud. Uploading data encrypted with FHE avoids this risk, while still providing the computing power of the public cloud. In many cases, data are stored in HDDs because the data size increases significantly when FHE is used. One important data analysis is Apriori data mining. In this application, two files are accessed alternately, and this causes long-distance seeking on its HDD and low performance. In this paper, we propose a new striping layout with reservations for write areas. This method intentionally fragments files and arranges blocks to reduce the distance between blocks in a file and another file. It reserves the area for intermediate files of FHE Apriori. The performance of the proposed method was evaluated based on the I/O processing of a large FHE Apriori, and the results showed that the proposed method could improve performance by up to approximately 28%.

Hadoop is a popular open-source MapReduce implementation. In the cases of jobs, wherein huge scale of output files of all relevant Map tasks are transmitted into Reduce tasks, such as TeraSort, the Reduce tasks are the bottleneck tasks and are I/O bounded for processing many large output files. In most cases, including TeraSort, the intermediate data, which include the output files of the Map tasks, are large and accessed sequentially. For improving the performance of these jobs, it is important to increase the sequential access performance. In this paper, we propose methods for improving the performance of Reduce tasks of such jobs by considering the following two things. One is that these files are accessed sequentially on an HDD, and the other is that each zone in an HDD has different sequential I/O performance. The proposed methods control the location to store intermediate data by modifying block bitmap of filesystem, which manages utilization (free or used) of blocks in an HDD. In addition, we propose striping layout for applying these methods for virtualized environment using image files. We then present performance evaluation of the proposed method and demonstrate that our methods improve the Hadoop application performance.

Two-track squeeze and adjacent track interference (ATI) are major barriers to increasing track density in hard disk drives (HDD). These depend on skew angles made by a magnetic head and circumferential direction on a magnetic disk. This paper describes relationships between the skew angle and the magnetic core width (MCW) which affects two-track squeeze and ATI performance. We propose a design concept of a track pitch profile at different skew angles considering MCW. Equivalent robustness of ATI performance on different skew angle conditions is obtained with the optimized track pitch.

A removable HDD “iVDR” is an international standardized medium, which has HDD features such as a large capacity and high-speed data transfer, and also is removable and compatible. We discuss the concepts of the hardware-specifications designed by the iVDR Consortium and the history of the international standardization activities for iVDR. We also discuss application expansions through these standardization activities.

A series of micromagnetic models including simulations of the 3D thin film write head field, the GMR read head, the thin film media and channel codes are utilized to study the recording performance in longitudinal hard disk drives (HDD) at extremely high densities. The (0, 4/4) encoder is utilized to translate the user data into (0, 4/4) constrained codes, before the write process is performed. The write current is achieved from the constrained code in the NRZ format. The read back voltage is reshaped to the PR-IV signal and the Viterbi detector is utilized to recover the data. In a medium of 10 nm grains, the recording linear density limits with the PRML method are about 1000 kfci, which is 1.5 times of those with the PD channel.

DC offset causes performance degradation in signal processing systems especially for high-speed applications. A new offset cancellation method that relaxes the requirement for the offset of the circuit components in the differential analog data path to about 10 times larger is introduced. This method moves the adjusting target from analog-to-digital converter (ADC) to its input buffer and adjusts DC level of ADC input to its center before the final offset cancellation. It eliminates post-production adjustment such as fuse trimming, which increases the cost and TAT in manufacturing and testing. Execution and simulation times are shortened down to 1/9 for less settling time in buffer and with improved logic. An automatic quick offset calibration circuit is implemented in a small silicon space in a high-speed hard disk drive (HDD) channel with 0.25-µm four-layer metal CMOS process. The measured data show this method works effectively in this system.

A dynamic measurement method of static R/W skew caused by MR-Inductive element alignment error is discussed. A geometrical model for the displacement between a write gap and a read gap on a swing arm is formulated. A measurement method wthich employs read-after-write procedure on disk surfaces in a drive is proposed. A simulation results is reported. It contributes to increase the track densities of HDDs using MR/Inductive heads in the region of more than 200 TPMM (5000 TPI).