High dimensional matrix algebra is essential in numerous signal processing and machine learning algorithms. This work describes a scalable square matrix-computing unit designed on the basis of circulant matrices. It optimizes data flow for the computation of any sequence of matrix operations removing the need for data movement for intermediate results, together with the individual matrix operations' performance in direct or transposed form (the transpose matrix operation only requires a data addressing modification). The allowed matrix operations are: matrix-by-matrix addition, subtraction, dot product and multiplication, matrix-by-vector multiplication, and matrix by scalar multiplication. The proposed architecture is fully scalable with the maximum matrix dimension limited by the available resources. In addition, a design environment is also developed, permitting assistance, through a friendly interface, from the customization of the hardware computing unit to the generation of the final synthesizable IP core. For N × N matrices, the architecture requires N ALU-RAM blocks and performs O(N 2 ), requiring N 2 + 7 and N + 7 clock cycles for matrix-matrix and matrix-vector operations, respectively. For the tested Virtex7 FPGA device, the computation for 500 × 500 matrices allows a maximum clock frequency of 346 MHz, achieving an overall performance of 173 GOPS. This architecture shows higher performance than other state-of-the-art matrix computing units.
This study reports experimental and numerical behaviors of both dry and silicon-coated twill-weave Kevlar fabrics under low-velocity impact. Initially, the fabrics are augmented in silicon aqueous suspension with various particle concentrations, and then, increase in the weight and friction coefficient are studied. The low-velocity impact test results show that the best particle concentration to meet the mentioned requirements is about 10 wt%. The experiments indicate high-impact resistance of the target by increase in the number of fabric plies. It is found that silicon-coated fabrics under drop-weight test show more time duration of impact and better performance than dry fabrics. Furthermore, the tests show that in the dry fabrics, broader region stretches due to impact, while in silicon-coated fabrics, the damage is limited to the impact point. The numerical simulation is performed for the coated fabric, and the effect of fabric augmentation with silicon is introduced as yarn friction. The numerical results are in good agreement with the experimental results.
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