XC7K420T-2FF901C_XC7Z030-3FFG676E Introduction

. AMD's stock price has risen 89% this year, and its current market value exceeds $100 billion, thanks to the new crown epidemic working from home to increase market demand for PCs, game consoles and other devices that use AMD chips. Xilinx, which has a market value of about $26 billion, has gained about 9 percent this year, slightly ahead of the S&P 500's 7 percent gain.

Recently, as the head of the CEO, Peng Rongkui introduced Cylinth's future vision and strategic blueprint for the first time, and released a new breakthrough product that surpasses FPGA-ACAP (AdaptiveCompute Acceleration Platform, AdaptiveCompute Acceleration Platform), which enables Cylinth Inspiration goes beyond the limitations of FPGAs to support the rapid innovation of many different technologies from end-to-edge to cloud. Since joining Xilinx in 2008, the company has won the championship for three consecutive times in the 28 nm, 20 nm and 16 nm three-generation process products, and won the first place in the industry. Broad application field development.

XC7K420T-2FF901C_XC7Z030-3FFG676E

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Since AMD launched the Ryzen 4000 series notebook platform APU processors at CES in January this year, in order to facilitate consumers to identify and search, the Zen 3 architecture processor series was directly named the 5000 series. A total of 4 CPUs were released this time, namely Ryzen9 5950X, Ryzen9 5900X, Ryzen7 5800X and Ryzen5 5600X.

Compared with the i5-10600K, the Ryzen 5 5600X is 19% higher in single thread, 20% higher in multi-threading, and 13% higher in 1080p gaming performance. Judging from the official comparison data, the new generation of Ryzen 5000 series processors is much stronger than the tenth-generation products of competitors: Ryzen 9 5900X is 13% higher than i9-10900K in single thread and 23% higher in multi-thread. %, 3% better gaming performance at 1080p. Compared with the i7-10700K, the Ryzen 7 5800X is 9% higher in single thread, 11% higher in multi-thread, and the 1080p game performance is the same. Among them, the Ryzen 9 5900X processor has been praised by AMD as "the best gaming CPU in the world" - this title has always been in the hands of Intel. The brand new architecture, the strongest game processor should come, and so on, the party has not waited in vain.

The array also contains an AI engine interface (on the bottom row) to facilitate interaction with other devices (PS, PL, and NoC) in the array. On current ACAP devices (eg, the VC1902 device), this array can contain up to 400 tiles. These AI engines can be arranged and combined into a two-dimensional array of AI engine tiles connected to memory, data streams, and cascaded interfaces. Introduction to the Xilinx AI Engine The AI Engine is included in some Xilinx Versal ACAPs.

It is a preconfigured, ready-to-run image for executing Dijkstra's shortest path search algorithm on Amazon's FGPA-accelerated F1. GraphSim is a graph-based ArtSim SSSP algorithm. The resulting archive conforms to the RFC 1952 GZIP file format specification. Go language to FPGA platform builds custom, reprogrammable, low-latency accelerators using software-defined chips. The GZIP accelerator provides hardware-accelerated gzip compression up to 25 times faster than CPU compression.

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XC7K420T-2FF901C_XC7Z030-3FFG676E

As current chip manufacturing processes become more complex and chip designs become more complex, initial costs for chip design manufacturers have skyrocketed, and the risks of tape have further increased. The need to reduce the cost of chips, reduce the risk of shooting, and shorten the time to market will further erupt. As a larger competitor, Altera has joined Intel in 2015, and Xilinx's new competitors have become Intel, NVIDIA and others. This is equivalent to the successful promotion of Xilinx, and will have higher competition with companies such as Intel and Nvidia. Against competitors like Intel and NVIDIA, you should focus on Xilinx's core competency, which is at the hardware level, it can be flexible and adaptable according to different workloads and forces, rather than traditional domain and competition.

The common data containers related to image operations in OpenCV are Mat, CvMat and IplImage. These three types can represent and display images. However, the Mat type focuses on calculation and is highly mathematical. While the CvMat and IplImage types are more focused on "images", OpenCV is optimized for image operations (scaling, single-channel extraction, image thresholding, etc.)