Maia 200: A Software Defined Dataflow System for Large-scale AI Acceleration

arXiv:2608.24664 · cs.AR, cs.AI, cs.DC, cs.ET, cs.LG · Submitted 2026-08-25 · Read on arXiv

cs.AR, cs.AI, cs.DC, cs.ET, cs.LG

Submitted: 2026-08-25

Updated: 2026-08-25

Terminology

• Decode — 5× in this paper · explained in 2 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Core — 4× in this paper · explained in 2 episodes
• Energy Efficiency — 4× in this paper · explained in 3 episodes
• KV cache — 4× in this paper · explained in 3 episodes
• Sparsity — 4× in this paper · explained in 4 episodes
• Tile Tensor Unit — 4× in this paper
• Abstraction — 3× in this paper · explained in 1 episode
• Accuracy — 3× in this paper · explained in 1 episode
• Mixture of Experts — 3× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Benchmarking — 2× in this paper · explained in 3 episodes
• Diffusion Model — 2× in this paper · explained in 8 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• Software Defined Locally Accessed Dataflow Architectures — 2× in this paper
• Activation Function — 1× in this paper · explained in 1 episode
• Agentic System — 1× in this paper · explained in 2 episodes
• Cluster Control Processor — 1× in this paper
• Device Control Processor — 1× in this paper
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Network on Chip — 1× in this paper
• Pruning — 1× in this paper · explained in 4 episodes
• RAG — 1× in this paper · explained in 3 episodes
• Remote Direct Memory Access — 1× in this paper
• Single Instruction Multiple Threads — 1× in this paper
• Steering — 1× in this paper · explained in 2 episodes
• Tensor Memory Accelerator — 1× in this paper
• Tile Control Processor — 1× in this paper
• Tile Vector Processor — 1× in this paper

Sources

• Reasoning Language Models: A Blueprint
• FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning
• FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
• The Llama 3 Herd of Models
• SpaDA: A Spatial Dataflow Architecture Programming Language
• Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks
• Ultra Ethernet's Design Principles and Architectural Innovations
• Demystifying NCCL: An In-depth Analysis of GPU Communication Protocols and Algorithms
• Data Movement Is All You Need: A Case Study on Optimizing Transformers
• Microscaling Data Formats for Deep Learning
• Qwen2.5 Technical Report
• FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision
• Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
• Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism
• Cognitive Architectures for Language Agents
• A System Level Compiler for Massively-Parallel, Spatial, Dataflow Architectures
• FlashAttention-4: Algorithm and Kernel Pipelining Co-Design for Asymmetric Hardware Scaling
• SGLang: Efficient Execution of Structured Language Model Programs

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