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Quality Circuit Assembly is a San Jose, CA-based company in the Computers and Electronics sector.
Pliops was founded in 2017 by flash storage industry veterans from Samsung, M-Systems and XtremIO. Pliops is creating a new category of product that enables cloud and enterprise data centers to access data up to 50X faster with 1/10th of the computational load and power consumption. Its technology collapses multiple inefficient layers into one ultra-fast device based on a groundbreaking patent-pending approach. Pliops` solution solves the scalability challenges raised by the cloud data explosion and the increasing data requirements of AI and ML applications.
Neocera is a Beltsville, MD-based company in the Computers and Electronics sector.
Founded in 2020, Mobix Labs Inc. provides True Xero™ latency connectivity solutions for 5G wireless and high-bandwidth cable networks. Based in Irvine, Calif., the company develops ultra-compact, fully integrated, single-chip, single-die, CMOS-based mmWave beamformers, antenna solutions and RF/mixed signal semiconductors necessary for mmWave 5G and next-generation wireless products. Mobix Labs also develops hybrid active optical cables, transceivers and optical engines for the data center, home entertainment and consumer electronics markets.
Our mission is to drive the future of edge computing with our FPGA silicon platforms. At the heart of our FPGAs is our disruptive Quantum™ fabric, which delivers a big Power-Performance-Area advantage over traditional FPGA technologies. Trion® FPGAs, offering 4K to 120K logic elements (LEs), have a small form factor, low power, are priced for high-volume production, and are available now in volume quantities. Taking it to the next level, Trion Titanium FPGAs have an enhanced Quantum compute fabric combined with a 16 nm process to give even lower power and higher speeds. With densities ranging from 25K LEs to 500K LEs, Titanium FPGAs are ready to meet your next design challenge. With their Power-Performance-Area advantage, Trion and Trion Titanium FPGAs address applications such as custom logic, compute acceleration, machine learning, and deep learning.