each token. In model deployment, this heavy KV cache is a large bottleneck that limits the maximum batch size and sequence length. 2.1.2. Low-Rank Key-Value Joint Compression The core of MLA is the low-rank 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 set to 2.4 × 10−4, and the gradient clipping norm is set to 1.0. We also use a batch size scheduling strategy, where the batch size is gradually increased from 2304 to 9216 in the training of the first 225B

workload into thread blocks (work groups) and individual threads (work items) Processing Element batch 二 (workitem) 2 下 罗汪| 门一一 Compute

tvm import relay 2. Load a pretrained network mod, params = relay.testing.mobilenet.get_workload(batch_size=1) 3. Partition and build the network with an external codegen mod = relay.build_extern(mod ator.py ● Apply the annotator to a workload: mod, params = relay.testing.mobilenet.get_workload(batch_size=1) mod[‘main’] = MyAnnotator().visit(mod[‘main’]) mod = relay.build_extern(mod, “dnnl”)© 2019 supported yet? ● Duplicated inputs optimization (e.g., reused parameters) ● Multiple outputs (e.g., batch normalization) ● Subgraph merging (e.g., conv2d + ReLU)© 2019, Amazon Web Services, Inc. or its Affiliates

enables importing of native ONNX models and those converted from Tensorflow. 5 ， Improve scheduling of batch matrix multiplies. 时”Early autotuning templates improve performance by ~20% e What we're working

Inc. or its Affiliates. All rights reserved. Performance Comparison • Metric – Latency in ms for batch size = 1 • 1.7x speedup on Inception asymmetric quantized model • Mobilenet requires depthwise convolution

reserved. Models with dynamism ● Control flow (if, loop, etc) ● Dynamic shapes ○ Dynamic inputs: batch size, image size, sequence length, etc. ○ Output shape of some ops are data dependent: arange, nms

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

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 matching graph 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 CPU CPU FPGA


 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