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Welcome to Zipcores IP Cores

Zipcores design and sell Intellectual Property (IP Cores) for implementation on Semiconductor Devices. We offer a wide range of cores for a variety of applications - from basic building blocks to more complex systems. Our IP Cores are supplied as VHDL source code (or Verilog on request) and can be synthesized across multiple technologies - whether it be FPGA, ASIC or SoC. Please click on a category to expand the list of available cores or contact us to discuss a custom solution.


Jul 18, 2023

After the aquisition of Xilinx by AMD, Zipcores is proud to announce its continued partnership and collaboration with AMD as an Adaptive Computing Partner. As such, we continue to offer solutions over the whole range of AMD (Xilinx) FPGA and SoC products - whether it be the low-cost 7-series portfolio, the current generation Ultrascale+ (16nm) devices, or the next generation Versal Adaptive SoC platforms.

If you are looking for help with IP Cores, hardware evaluation or a general custom solution relating to AMD products then please fill out our customer support form and we'd be happy to help. Please see the following link for more info at: Zipcores Support.

Zipcores AMD Adaptive Computing Partner

Feb 9, 2023

Introducing our new ZIP-FMC-SDI Mezzanine card with dual, independent SDI inputs and dual loop-through outputs. Includes cable equalization/amplification and full pixel clock recovery. Supports 3G-SDI/HD-SDI/ED-SDI/SD-SDI and DVB-ASI stream up to HD1080p60 resolution. No high-speed Gbit transceivers required as the SDI deserialization is built into the design. Features a simple LVDS interface ideal for ALL eval boards. Examples include low-cost boards from AMD/Xilinx® using Zynq-7000 and Spartan-7 devices such as ZC702, ZedBoard, MicroZed, SP701, etc.

Zipcores' FMC-SDI Mezzanine card

Nov 24, 2022

Looking for a cost-effective On-Screen Display (OSD) solution for real-time video applications? Well look no further! Zipcores offers a range of versatile and functional text and graphics overlay IP Cores with very simple interfacing and no complex programming required. Our Text overlay and GPU overlay IP Cores may be programmed in real-time via an external MCU/uP or embedded processor. Simple programming interfaces such as UART, I2C or SPI are also offered for ease of product integration.

Zipcores OSD IP Cores are ideal for a wide range of interactive applications such as HUDs, menus, lists, charts, gauges, tables, counters, timers, clocks etc. All FPGA, SoC and ASIC technologies are supported with no external frame buffer memory required.

On-Screen Display (OSD) IP Cores from Zipcores

Oct 1, 2021

A new project at the Instituto de Astrofísica de Canarias (IAC, "QUIJOTE"), intended to study Deep Space Cosmic Background Radiation, is making use of our FMC breakout card. Together with a Xilinx® Zynq-7000 base board (ZEDboard), our FMC Card is being used for the interfacing and control of a 256 channel x 24-bit data acquisition system. The system uses an array of small microwave antennas and a bank of high-res 24-bit AD7768 ADCs from Analog Devices.

Engineer, Sergio Gonzalez, adds: "The success of our work with IAC continues with the ZIP-FMC-BRK card and it's proving to be a very useful prototyping platform during tests. The IAC research project will study very deep space (20-100 GHz) residual radiation and its anisotropy."

FMC-BRK card

Dec 11, 2020

Professor Ming C. Wu's group at the University of California, Berkeley, has chosen Zipcores' ZIP-FMC-DSP Mezzanine card for their research into machine learning using photonics. Philip Jacobson, key PhD researcher at Berkeley explains:

"Given our reliance on analog electronics, we're using an FPGA with the Zipcores FMC card to control the data I/O within our system. This FMC card allows us to sample at high speed using a low-cost, low-power PicoZed platform. The FMC card has proven critical for the demonstration of complicated machine learning tasks like image recognition.

Ultimately, the goal of our work is to develop novel, high-speed, low-power machine learning platforms by leveraging photonics. Our work is based on the reservoir computing paradigm, in which an electro-optic modulator with delayed feedback is used to perform classification tasks".

You can learn more about UC Berkeley EECS department and their research projects just here.

Berkeley chooses Zipcores' FMC-DSP card

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