Eyal Amiel

Title: Eyal Amiel: Innovator in Associative Processing

Introduction

Eyal Amiel is a notable inventor based in Rosh-Ha′ayin, Israel. He has made significant contributions to the field of associative processing, holding a total of 2 patents. His work focuses on advanced computational methods that enhance the efficiency of processing units.

Latest Patents

One of Eyal's latest patents is titled "Square root calculations on an associative processing unit." This method involves calculating a square root B of a number X by iterating on the bits of square root B, starting from the most significant bit. The process includes locating a 1 at the squared location of bit b in a CHECK variable and determining the value of bit b based on comparisons with previously found bits. This innovative approach streamlines the calculation process in associative processing units.

Another significant patent is "Concurrent multi-bit subtraction in associative memory." This method describes an associative memory device that stores pairs of multi-bit operands in a memory array. The device utilizes bit-lines to read and write values, allowing for concurrent multi-bit addition operations. This technique provides an efficient way to compute the difference between operands X and Y across multiple columns.

Career Highlights

Eyal Amiel is currently employed at GSI Technology, Inc., where he continues to develop innovative solutions in the field of associative processing. His expertise in computational methods has positioned him as a valuable asset to the company.

Collaborations

Eyal has collaborated with notable colleagues, including Moshe Lazer and Samuel Lifsches. Their combined efforts contribute to the advancement of technology in associative processing.

Conclusion

Eyal Amiel's contributions to the field of associative processing through his patents and work at GSI Technology, Inc. highlight his innovative spirit and dedication to advancing technology. His methods for square root calculations and multi-bit subtraction are paving the way for more efficient computational processes.