XC7Z030-L2FFG676E_XC7Z010CLG400 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.

XC7Z030-L2FFG676E_XC7Z010CLG400

XC7Z045-3FFG676C

XQ4VLX60-10EF668M XQ4VLX40-10FFG668M XQ4VLX40-10FF668I XQ4VLX25-DIE4058 XQ4VLX25-11SF363M XQ4VLX25-10SFG363M XQ4VLX25-10SF363M XQ4VLX25-10SF363I XQ4VLX25-10FF668M XQ4VLX25-10FF668I XQ4VLX160-10FF1148I XQ4VLX100-10FF668M XQ4VLX100-10FF1148M XQ4VLX100-10FF1148I 。

XQ4013E-5PG223M XQ4013E-4PG223M XQ4013E-4HQ208N XQ4013E-4CB228M XQ4013E-4CB196N XQ4013E-3HQ240N XQ4013E-3CB196N XQ4013E-3CB191M XQ4013E-3BG191M XQ4013-5PG223M XQ4013-4PG223M XQ4010EX-4PG191M XQ4010EX-4HQ191N XQ4010EX-4CB196N XQ4010EX-4CB196M XQ4010EX-4CB191N 。

XQ4010E-4PG196M XQ4010E-4PG191M XQ4010E4PG191M XQ4010E-4PG191G XQ4010E-4PG191CMM XQ4010E-4PG191B XQ4010E-4HQ191M XQ4010E-4CB196N XQ4010E-4CB196M XQ4010E-4BG191M XQ4010E-3PG196N XQ4010E-3HQ208N XQ4010E-3HQ196M XQ4010E-3HQ191M 。

XQ5VFX100T-1EF1136M XQ5VFX100T-1EF1136I XQ5VFX100T XQ4VSX55-10FFG1148M XQ4VSX55-10FF1148M XQ4VSX5510FF1148M XQ4VSX55-10FF1148I XQ4VSX55-10CF1148M XQ4VSX35-9FFG668I XQ4VSX35-9FF668I XQ4VSX35-10FFG668IES XQ4VLX80-11FF1148I XQ4VLX60-10FFG1148M XQ4VLX60-10FF668M XQ4VLX60-10FF1148M 。

XC7Z030-L2FFG676E_XC7Z010CLG400

XC7Z020CLG400

XQR18V04CC44V XQR18V04CC44M XQR17V16VQ44R XQR17V16VQ44N XQR17V16-DIE0628 XQR17V16CK44V XQR17V16CK44M XQR17V16-CC44V XQR17V16CC44V XQR17V16CC44M XQR1701LCC44V XQR1701LCC44MES XQR1701LCC44M XQF32PVOG48M XQF32PVOG48C XQF32PVOG48 XQF32P-VO48M 。

XQVR2V300-4CB228V XQVR1000-4CG560V XQVR1000-4CG560M XQVR1000-47J560N XQV95288XL-7BG256N XQV812E-7FG900N XQV812E-6BG560N XQV800E-6FG680N XQV800E-6FG676N XQV800E-5PQ240N XQV800E-5HQ240N XQV800E-3BG560N XQV600E-6FG900N XQV600E-6FG680N 。

XQ7A200T-1RS484I XQ6VSX475T-L1RF1759I XQ6VSX475T-L1RF1156I XQ6VSX475T-L1FFG1156I XQ6VSX475T-3FFG1156I XQ6VSX475T-2FFG1156I XQ6VSX475T-1RF1759I XQ6VSX475T-1RF1156I XQ6VSX475T-1FFG1156I XQ6VSX315T-L1RF1759I XQ6VSX315T-L1RF1156I XQ6VSX315T-L1FFG1156I XQ6VSX315T-2RF1759I XQ6VSX315T-2RF1156I XQ6VSX315T-2FFG1156I 。

XQR2V6000-4CF1144H XQR2V60004CF1144H XQR2V3000CG717AGT0822 XQR2V3000-5BG728R0916 XQR2V3000-4CG717V0119 XQR2V3000-4CG717V XQR2V3000-4CG717M XQR2V3000-4CF717V XQR2V3000-4CF717M XQR2V3000-4BG728R XQR2V3000-4BG717V XQR2V1000-4FG456R XQR2V1000-4FG456N XQR2V1000-4BG575R XQR2V10004BG575R XQR2V1000-4BG575N 。

XC7Z030-L2FFG676E_XC7Z010CLG400

The I/O and clock circuits account for 1/3 of the total active power consumption, and the power consumption can be even higher if high-power I/O standards are used. According to the report, active power consumption is the power consumption when the design is active at high temperature, including dynamic and static power consumption. Figure 2 shows an exploded view of the active and standby power consumption of the XC3S1000. Standby power is the power consumption when the design is idle and consists of static power consumption at rated temperature. It's no surprise that the CLB accounts for the largest portion of active and standby power, but other modules also generate considerable power.

We use the example of fast corners to illustrate the process of implementing OpenCV with VivadoHLS. Next, establish the OpenCV processing algorithm based on the video data stream chain, and rewrite the usual design of the previous OpenCV. This rewrite is to be the same as the HLS video library processing mechanism, which is convenient for the function replacement in the following steps. Of course, these synthesizable codes can also run on a processor or ARM. Finally, the functions in the rewritten OpenCV design are replaced with video functions of the corresponding functions provided by HLS, and synthesized using VivadoHLS, implemented in FPGA programmable logic or as a Zynq SoC hardware accelerator under the Xilinx development environment. First, develop an OpenCV-based fast corner algorithm design and validate this algorithm using OpenCV-based test-inspired simulations.