class AccelModule:© Copyright 2018 Xilinx TVM Partitioning >> 7 Subgraph 1 Parallel Subgraphs Post-Processing Pre-Processing FPGA or CPU FPGA CPU CPU FPGA - More than supported/not supported, pattern Subgraph 1 Parallel Subgraphs Post-Processing Pre-Processing CPU FPGA CPU CPU FPGA© Copyright 2018 Xilinx TVM Code Generation >> 9 Subgraph 1 Parallel Subgraphs Post-Processing Pre-Processing CPU FPGA FPGA CPU CPU FPGA Parallel Subgraphs© Copyright 2018 Xilinx Registering external accelerator function @reg.register_compute("accel", level=15) def compute_accel(attrs,inputs,outputs): op = 'accel'

Models Led To… *A FLOP (floating point operation) is a basic unit of computation used to measure processing power, representing a single arithmetic calculation involving decimal numbers. In AI, total FLOPs on some reasoning tests 3/23: OpenAI releases GPT-4, a multimodal* model capable of processing both text & images 3/23: Google releases Bard, its ChatGPT competitor 11/23: 28 countries Ecosystem Tells Over Four Years = >100% Growth in Developers / Startups / Apps Note: GPU = Graphics Processing Unit. Source: NVIDIA (2021 & 2025) NVIDIA Computing Ecosystem – 2021-2025, per NVIDIA 2.5MM

Pre-Training 3.1. Experimental Setups 3.1.1. Data Construction While maintaining the same data processing stages as for DeepSeek 67B (DeepSeek-AI, 2024), we extend the amount of data and elevate the data further improve the training efficiency, we overlap the computation of shared experts with the expert parallel all-to-all communication. We also customize faster CUDA kernels for communications, routing algorithms following engineering optimizations. (1) Firstly, we propose a hybrid engine that adopts different parallel strategies for training and inference respectively to achieve higher GPU utilization. (2) Secondly

generate HVX instruction 。， Add one Hexagon runtimes named as libtvm_hexagon_runtime.so to support parallel. 。 Could run end-to-end TFLite Mobilenet V2 quantized model on Simulator / Device. /NiiOS ! 驱动万物智能


 extracting meaning from documents, or interacting with 
 users conversationally, for example processing a home insurance claim. Before committing to building an agent, validate that your use case can Agent" "You assist clients with inquiries regarding order tracking, delivery schedules, and processing returns or refunds." 22 A practical guide to building agents 26 27 28 29 30 31 32 33

prompt’s writing style and structure in relation to the task. In the context of natural language processing and LLMs, a prompt is an input provided to the model to generate a response or prediction. Prompt use in applications, requires significantly more tokens than plain text, leading to increased processing time and higher costs. Furthermore, JSON's verbosity can easily consume the entire output window

Blocking Splits the workload into thread blocks (work groups) and individual threads (work items) Processing Element batch 二 (workitem) 2