In today's AI enhanced vehicles, ADAS systems are enhancing safety and driver experience. They use data from various sensors like cameras, radar and LiDAR. and process and analyze them to enable features such as collision avoidance, automated driving parking assist, driver and passenger monitoring, object and sign detection and identification, and so on.Now, looking in the future. Real time sensing and communication will be vital for orchestrating ADAS seamlessly across interconnected vehicles and roadway i ...

In today's AI enhanced vehicles, ADAS systems are enhancing safety and driver experience. They use data from various sensors avoidance, automated driving, like cameras, radar and LiDAR, and process and analyze them to enable features such as collision parking assist, driver and passenger monitoring, object and sign detection and identification, and so on. Now, looking in the future.Real time sensing and communication will be vital for orchestrating ADAS seamlessly across interconnected vehicles and roadway ...

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As a leader in embedded computing, AMD empowers developers and engineers to unlock the full potential of AI at the edge. Our embedded portfolio of adaptive SoCs and x86 processor solutions are designed to accelerate insights from data, enabling real-time decision-making, ensuring you maximize productivity and innovation in every project, across industrial, healthcare, space, automotive and more. 🎥 Dive into our latest video to see how we’re pioneering AI innovation at the edge and setting the standard for w ...

Overview - The Vitis Unified IDE is a development environment for AMD Adaptive SoCs and FPGAs application creation [1] - The video demonstrates the Vitis Embedded development flow and navigating the new Vitis Unified IDE [1] Development Process - Creating the platform and a "hello world" application within the Vitis Unified IDE [1] - Setting up target connections and deploying on the target board [1]

Software Development & FPGA Acceleration - Vitis HLS 2023.1 introduces a new L1 library wizard [1] - The wizard facilitates downloading, viewing, and instantiating L1 library functions within the Vitis HLS GUI [1] - The report focuses on learning about Vitis L1 libraries [1]

AI Engine Rapid Prototyping Overview - AMD introduces the Versal AI Engine Rapid Prototyping using the AMD Vitis Unified IDE for early design analysis and risk reduction [1][2][12][13] - The rapid prototyping feature is available in the Vitis Unified IDE in version 20242 [13][16] Key Steps in Rapid Prototyping - Involves resource estimation, including tile count, buffer usage, PLIO resources, and stream array traffic [2] - Assesses latency and throughput feasibility with early data flow simulations, prototype kernel coding, and initiation interval loop analysis [2] - Utilizes Vitis libraries for existing block elements and develops candidate vectorization options [3] - Includes building empty kernel wrappers, building the graph and compiling, simulating and analyzing for early estimation [12] Custom Kernel Example: Digital Up Conversion (DUC) Chain - The DUC chain translates a signal from baseband to intermediate frequency band and includes a FIR fractional resampler, half-band interpolators, DDS mixer functions, and an adder functional block [5] - The FIR fractional resampler, the half-band interpolators, and DDS mixer functions can be implemented using the Vitis DSP Library [5] - Focuses on fast prototyping of the custom adder kernel, identifying input/output data types, coefficient types, number of taps, sampling rate, and the kernel function [6] AI Engine System Mapping - Identifies hardware resources such as the number of AI Engine tiles, storage, buffers, and connectivity ports [8] - Considers compute (AIE tiles), storage (buffer size, local memory, DMA size), and input/output bandwidth (PLIO ports, clocking, buffer/stream interfaces) [8] - A custom adder kernel requires a sampling rate of 1200 MSPS with a latency less than 500 ns [9] - The adder is implemented in one tile with two inputs and one output of cint16 type, taking 3KB of data at a sampling rate of 1200 MSPS [10][11] Vitis Unified IDE Implementation - Generates data flow models with parametrized kernel ports, multi-core graph topology, full buffering, stream details, and LUT storages [14] - Allows exploration of hardware utilization through AI Engine compilation and ensures throughput and latency requirements are met through AI engine emulation [14] - Requires creating a new empty AI engine component and using the "Generate AIE Prototype Code" option [15] - Involves setting kernel properties such as name, input/output port properties (data type cint16, dimension to 384 samples), and enabling "Generate Top Level graph and Simulation code" [19][20] Simulation and Analysis - The tool generates graph CPP and H files, with the graph CPP setting the graph to run for one iteration (modifiable for better analysis) [20][21] - Requires adding input text files for simulation, containing values representing cint16 samples per clock on the 64-bit interface [22][23][24][25] - Simulation results report a throughput of 5000 megabytes/second or 1250 mega 16-bit complex samples per system, meeting the requirements [26]

Key Features of AMD Vitis Unified IDE - AMD Vitis Unified IDE utilizes Eclipse Theia framework, offering a modern and responsive GUI to enhance user experience [2] - The IDE supports a bottom-up design flow, enabling the development of system components like AI Engine graphs, C/C++ sourced HLS components, RTL kernels, and software applications [2] - It provides integrated revision control using Git and Python, along with a Tcl script-based interface for command-line component management [3] HLS Component Development - HLS component development is streamlined through a bottom-up design flow managed with a configuration file [3] - The IDE facilitates independent building, simulation, analysis, and debugging of HLS components [3] - Tools like component cloning allow for design optimization exploration, while component comparison provides insights into performance and resource utilization [4] - Code analyzer offers capabilities for architectural refinement [4] Migration Flows from Classic Vitis HLS - Migration from classic Vitis HLS designs to the Unified IDE is possible via GUI, command-line, and scripting [4] - In GUI, specify the hls app file from the classic Vitis HLS project when creating an HLS component [5] - For Tcl scripting, replace `open_project` with `open_component` and remove `open_solution`; specify `-flow_target` as either `vivado` or `vitis` [6] - Python APIs are available for creating and managing HLS components, with configuration specified in a file or directly in the script [8]

HLS Design Flow in Vitis Unified IDE - The AMD Vitis Unified IDE supports a bottom-up approach for heterogeneous system design, enabling the creation of individual system elements as components [2] - The IDE offers various development flows, including HLS, AI Engine Graph, Embedded, and System Development, along with tools for report analysis and user-managed workflows [2] - The Vitis Components view provides hierarchical project navigation, organizing source files and test benches [14] HLS Component Creation and Configuration - An HLS component can be created using the 'Create HLS Component' wizard, which guides users through the process [3] - The HLS component configuration file stores commands and settings for synthesis, simulation, and export [6] - Users can specify the top-level function to be synthesized, with underlying functions also synthesized into RTL [9] - The tool automatically applies uncertainty margin during synthesis to create RTL that is more likely to meet timing in Vivado [11] - The flow target can be set to either 'Vivado IP' or 'Vitis kernel', with the default 'Vivado IP' setting generating a .zip file [11][12] Verification and Packaging - C simulation can be run with default settings, generating a summary report and simulation log file [16][17] - RTL cosimulation verifies the generated RTL against the C test bench to ensure identical results [20] - The design can be packaged into a reusable IP component, with options for Vivado IP, Vitis kernel (.xo file), or RTL output [22][23][24][25] RTL Analysis and Implementation - HLS provides estimations for resource utilization and timing, but accurate RTL analysis requires running Vivado RTL synthesis and place-and-route [25][26] - Vivado synthesis and implementation can be configured before execution using the Implementation settings [26]

Product & Technology - AMD is developing a chip with a focus on power, performance, and area (PPA) [1] - AMD has products supporting AI, which is considered a significant technology with the potential to transform lives by enabling users to perform tasks beyond their expertise [2] - Methodology serves as a recipe for design teams to achieve good PPA, allowing for easy initial setup and further customization, benefiting the entire company [1] Strategy & Culture - Badminton is viewed as a strategic game that helps with relaxation and focus for work [1][2]