Core Viewpoint - The company has fully integrated AI algorithms into its products, enhancing various operational processes such as component positioning, defect detection, and automatic programming [1] Group 1: AI Integration - The company has implemented AI algorithms across multiple products including AOI, SPI, AXI, and dispensing systems [1] - The applications of these AI algorithms are extensive, covering areas like component positioning, defect detection, and automatic programming [1] Group 2: Motion Control - The company has developed an adaptive transmission system for the MCB control board, utilizing deep learning algorithms [1] - This system allows for precise control based on the stop state of different PCB substrates [1]

Debugging Flows & Tools - The industry utilizes a four-step debug process: probing, implementing, analyzing, and fixing [1][2][3] - AMD provides ChipScope debug solution to reduce verification and debugging time, maximizing visibility into programmable logic during system operation [3] - Vivado Logic Analyzer (VLA) interacts with debug cores for triggering and data collection via JTAG pins, supporting various triggering scenarios and flexible probing [4] - Captured data can be reused as test vectors, enhancing design verification, and a single JTAG connection simplifies programming and debugging [5] - Debug cores like Integrated Logic Analyzer (ILA), System ILA, Virtual Input/Output (VIO), and JTAG to AXI Master enable design visibility without obstructing functionality [6] Debug Cores & Features - Integrated Logic Analyzer (ILA) IP core monitors internal signals with advanced features like Boolean trigger equations and edge transition triggers, configurable with up to 1024 probe ports [7] - Virtual Input/Output (VIO) core monitors and drives internal signals in real time, presenting data as virtual LEDs, pushbuttons, or toggle switches [9][10] - JTAG to AXI Master debug feature generates AXI transactions to interact with AXI-Full and AXI-Lite slave cores [11][12] - BSCAN to JTAG Converter core bridges BSCAN and JTAG interfaces for designs supporting JTAG but not BSCAN [13][14] Data Cables & Debug Ports - Platform Cable USB II is a general-purpose cable for programming and debugging, supporting devices with target clock speeds from 750 kHz to 24 MHz via USB 20 [15] - SmartLynq Data cable provides JTAG rates up to 40 Mb/s via Ethernet and USB, supporting JTAG debugging and indirect flash programming [16][17] - SmartLynq+ is designed for high-speed debugging and tracing in Versal Adaptive SoCs, offering trace capture speeds up to 10 Gb/s and up to 14 GB of trace memory [19][20] Probing Flows & Methodologies - HDL instantiation flow involves manual customization and connection of debug cores directly in the HDL design source, requiring re-running synthesis and implementation [22][23] - Netlist insertion flow inserts ILA cores directly into the netlist, eliminating design resynthesis and allowing probing at various design levels [23][24] - Incremental Compile Flow allows modifying debug cores while reusing 95% of prior placement and routing results [36] - ECO Flow focuses on replacing existing debug nets with minimal changes, preserving previous implementation results [37][38] ChipScoPy - ChipScoPy provides a Python interface to program and debug Versal devices, with a 100% Python code base available on githubcom [39] - ChipScoPy enables high-level control of Versal debug IPs, allowing developers to control and communicate with cores like ILA and VIO [39][40]

不同的变量，因此那里有很大的灵活性。在芯片领域也不例外。但你需要针对具体应用和目标市场 进行调整，以达到功率、性能和面积。一旦你确定了这一点，你就可以从内而外地开始工作了。" 所有芯片组的系统总线必须相同。"在理想情况下，I/O 互连是通用的，可以完美连接，我们希望有 这给小芯片子系统领域的 IP 供应商增加了复杂性和新的挑战，因为他们需要不断适应客户群的新变 化。 目标市场 如果您希望可以时常见面，欢迎标星收藏哦~ 来源：内容 编译自 semiengineering ，谢谢。 随着芯片超越大型芯片制造商的专有设计并与封装或系统中的其他元素进行交互，管理芯片资源正 成为一项重大而多方面的挑战。 芯片中资源管理不善为通常的功率、性能和面积权衡增加了一个全新的维度。它可能导致性能瓶 颈，因为当芯片跨边界通信时，其固有延迟比单个芯片内更长。它还可能增加开发成本，因为添加 到系统中的每个芯片也会在多个层面上增加复杂性。它还会影响功耗，随着设计中的芯片数量增加 且必须不断相互通信，功耗变得更难管理。 最大的系统和处理器供应商已经有效地使用了这种方法，通过增加计算密度来提高性能，通过提高 产量来降低成本。但使用第三方芯片 ...