XC7Z030L2FBG676I_XC7Z010CLG225 Introduction

Xilinx, Inc. (NASDAQ: XLNX), the global leader in adaptive and intelligent computing, today announced the Zynq RFSoC DFE, a new class of breakthrough adaptive radio platforms designed to Meet evolving 5G NR wireless application standards.

On the other hand, AMD and Xilinx have been working closely together for a long time. A series of storage system-oriented IPs such as NVMe HA, NVMe TC and Embedded RDMA previously provided for AMD EPYC (Xiaolong) data center processors can help AMD build low latency The high-efficiency data path, thus realizing the efficient storage acceleration function of FPGA. In fact, a similar plot was staged as early as 2015, when Intel (Intel) acquired FPGA manufacturer Altera for $16.7 billion, and Altera also followed the trend for Intel's follow-up "CPU+xPU (GPU+FPGA+ASIC+ eASIC)” strategy provides the most solid foundation.

XC7Z030L2FBG676I_XC7Z010CLG225

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XC7Z030L2FBG676I_XC7Z010CLG225

In openCV, the CvMat and IplImage types are more focused on "images", especially with a certain degree of optimization for image operations in them. OpenCV does not have a data structure for vectors, but when we want to represent vectors, we need to represent them with matrix data. However, CvMat is more abstract, and its element data types are not limited to basic data types, but can be any predefined data types, such as RGB or other multi-channel data.

Taking Xilinx Spartan-3 XC3S1000 FPGA as an example, assume that the clock frequency is 100MHz, the inversion rate is 12.5%, and the resource utilization rate is the typical value of various actual design benchmarks. Let's analyze the decomposition of the total power consumption of the FPGA in order to understand the main power consumption. FPGA power consumption is design-dependent, that is, depends on device family, clock frequency, toggle rate, and resource utilization.