![]() ![]() In fact, calling it the age of “No Longer Programmable Logic” beyond 2015 may be appropriate. ![]() Trimberger’s article, published in the March 2015 IEEE Proceedings, names three ages in this succession:įollowing the “Age of Accumulation” through 2015, the author submits that FPGA technology entered the age of “No Longer Programmable Logic.” Ironically, the title contradicts the essence of the device as captured in its name, but it reflects the reality of its contents. and Xilinx fellow, titled “The Three Ages of FPGAs: A Retrospective on the First Thirty Years of the FPGA Technology,” traces the evolution of the FPGA from its origin in 1984 to 2015. 【Download】Cybersecurity: the case for hardware-based threat detection and mitigationĪn article by Stephen M. Figure 1: Today’s FPGA is a complex set of hardware blocks, including programmable logic, application and real-time processors and blocks of interface controllers that is more of an adaptive compute acceleration platform. Prominent among AI applications is deep-learning acceleration (DLA). Lately, the FPGA renaissance has been bolstered by progress in Artificial Intelligence (AI) technologies and proliferation of AI applications. In later years, a wide range of automotive, military, consumer and defense applications have been using FPGAs. Oddly, its very versatility is creating a dilemma for FPGA vendors.Ĭommunications and networking stood out among applications that drove the FPGA’s early popularity because of frequent changes in their standards that necessitated field updates/grades, inconceivable with hard-wired ASIC implementations. Today, it is more popular than ever before, reinvigorated by its intrinsic raw processing power and adaptability, a perfect match for accommodating the rapid evolution of the electronic industry. The 35-year-old field programmable gate array (FPGA) is one of the most impressive semiconductor devices ever created, short of the central processing unit (CPU). To be fair, Synopsis have much more experience at this than most, so using their formula is probably about as good as a rough estimate can be.There are two distinct and very different technological paths for FPGAs, and that is creating a dilemma for FPGA vendors. When Xilinx reports LUT2/3/4 etc, thats just the number of inputs used in a given LUT6 on the fabric. (This also doesnt take into account LUT packing, which is where the synthesis might decide it can pack two separate parts of your RTL into a single LUT) For two separate 100k gate ASICs, one might fit in a given FPGA and the other wont. Because of this gate equivolence is pretty meaningless. So what might be 10 gates in an asic might fit in a single LUT in the FPGA or it might take 10. all LUTs have 6 inputs.īut, all that means is each lut can have anywhere from 1 (for a simple inverter) to 6 inputs (for a multi-gate LUT). Is it indicating that I combine all the LUT* counts from my synth report and use that value in comparing with the gate equivalent count? Because in Xilinx devices we have LUT1, LUT2, LUT3, LUT4, LUT5 and LUT6. What I don't understand is what is exactly meant by "LUT". It says, 1* LUT = 6 Two input NAND Gate equivalent (go try it!) I have referred to this 2015 blog from Synopsys and there is a reference to Xilinx in it: ![]() How do I find that? How can I *roughly* map the gate equivalent count to the LUTs count? Any suggestions? Now lets assume that someone asks me if I can find out how many LUTs will be utilized if I want to implement a 100,000 gate ASIC in a Ultrascale or a 7 series Xilinx FPGA. The synth report will contain the amount utilized by each of these LUTs. Now there are stuff like LUT1, LUT2, LUT3, LUT4, LUT5 and LUT6. I am particularly interested in the number of LUTs utilization counts (lets us ignore the BUF*, MMCM/PLL, DSP-slices, BRAMs, etc). We all know that the synth report contains a table that contains the number of resources utilized. ![]()
0 Comments
Leave a Reply. |