High-Performance computing of Real-Time and Multi-Channel Histograms: a Full FPGA Approach

In a world heading towards applications, in science and industry, based on big data processing, the ability to elaborate streams of data is becoming more important every day. Applications of various natures, ranging from biology to chemistry, from medical imaging to spectroscopy, need systems able to detect, process and store huge amounts of data in real-time. In this context, techniques such as histogramming come into play. Histograms are able to represent data shapes and retrieve statistical information, favoring further processing. This kind of processing is usually done with the help of general purpose processors, relying on temporal computing, with their pros (simplicity and fast operating frequencies) and cons (inability to exploit parallel computation). Both Industry and Academia have, however, proposed many solutions to this need, delivering histogram generators both in full-custom Application-Specific Integrated Circuits (ASICs) and Field-Programmable Gate Array (FPGA) IP-Cores, preferred over processors thanks to their superior parallel computing power. In this work, we present a full FPGA approach to this issue, resulting in a high-performance IP-Core for generating and managing multiple histograms in real time, each supporting a data flow up to 224 MSps, with a strong focus on overall flexibility and area efficiency, using as low as < 250 LUTs and 300 FFs resources for a 16 bit-wide, 4096-bin histogram implementation. The IP-Core has been successfully integrated and validated in a high-performance time-mode application: an FPGA-based Time-to-Digital Converter. The resulting IP-Core is, more in general, a single solution perfectly adaptable to any field of application and FPGA device