Abstract The SHA-256 algorithm is one of the most widely used secure hashing algorithms. The SHA-256 algorithm is implemented in hardware, and in order to ensure the integrity and authenticity of the encrypted data, this requires higher throughput and efficiency. In this paper, we propose a high-performance hardware architecture for the SHA-256 hash algorithm, which further optimizes the rearranged round computation by decomposing the critical path into two addition stages and replacing the multi-operator adder in the critical path of the algorithmic round-computing circuit with a 4-2 compressor. Based on the experimental results on field-programmable gate arrays, the obtained result shows a significant improvement in the performance of the proposed SHA-256 algorithm when compared with various existing architectures. Its maximum clock frequency is 366 MHz, with a throughput of 1990 Mbps and an improved efficiency of 1.86 Mbps per slice.

SUMMARY: With the advance of genomic sequencing techniques, chromatin accessible regions, transcription factor binding sites and epigenetic modifications can be identified at genome-wide scale. Conventional analyses focus on the gene regulation at proximal regions; however, distal regions are usually less focused, largely due to the lack of reliable tools to link these regions to coding genes. In this study, we introduce RAD (Region Associated Differentially expressed genes), a user-friendly web tool to identify both proximal and distal region associated differentially expressed genes (DEGs). With DEGs and genomic regions of interest (gROI) as input, RAD maps the up- and down-regulated genes associated with any gROI and helps researchers to infer the regulatory function of these regions based on the distance of gROI to differentially expressed genes. RAD includes visualization of the results and statistical inference for significance. AVAILABILITY AND IMPLEMENTATION: RAD is implemented with Python 3.7 and run on a Nginx server. RAD is freely available at https://labw.org/rad as online web service. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.