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Fast Parallel Similarity Calculations with FPGA Hardware

Published by TigerGraph

This whitepaper explores how TigerGraph leverages FPGA hardware to significantly accelerate graph-based similarity calculations, enhancing real-time data analytics and recommendation engines. By integrating Field Programmable Gate Arrays (FPGAs) with TigerGraph’s User Defined Functions (UDFs), businesses can process vast datasets in parallel, reducing the time for similarity computations from hours to milliseconds. The paper highlights the importance of these calculations in applications like healthcare, fraud detection, and recommendation systems. FPGA's parallel processing capabilities allow for real-time insights, driving faster decision-making and improving overall system performance.

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