mlsanityData to 7 Oct 2026

Challenges and Research Directions for Large Language Model Inference Hardware

arXiv 2601.05047 ↗First posted 8 Jan 2026cs.AR cs.AI cs.LGcited by 10

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Abstract (arXiv)

Large Language Model (LLM) inference is hard. The autoregressive Decode phase of the underlying Transformer model makes LLM inference fundamentally different from training. Exacerbated by recent AI trends, the primary challenges are memory and interconnect rather than compute. To address these challenges, we highlight four architecture research opportunities: High Bandwidth Flash for 10X memory capacity with HBM-like bandwidth; Processing-Near-Memory and 3D memory-logic stacking for high memory bandwidth; and low-latency interconnect to speedup communication. While our focus is datacenter AI, we also review their applicability for mobile devices.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 3 of its 14 references that are in the map. First posted on arXiv 8 Jan 2026.

Builds on

3 of 14 references.

References · 3

  1. 2024Duplex: A Device for Large Language Models with Mixture of Experts, Grouped Query Attention, and Continuous Batchingcited by 33
  2. 2021Benchmarking a New Paradigm: An Experimental Analysis of a Real Processing-in-Memory Architecturecited by 9
  3. 2025Managed-Retention Memory: A New Class of Memory for the AI Eracited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 10.

10 papers.

  1. 2026Dynamic Expert Sharing: Decoupling Memory from Parallelism in Mixture-of-Experts Diffusion LLMscited by 4
  2. 2026A Practical Investigation of Training-free Relaxed Speculative Decodingcited by 2
  3. 2026Potential Applications of HBF in LLM Serving Systemscited by 2
  4. 2026LLM Inference in a Flash!cited by 1
  5. 2026HBFlex: A Flexible Memory System for Bridging Fine-Grained LLM States and Coarse-Grained HBF Parallel Executioncited by 1
  6. 2026AMMA: A Multi-Chiplet Memory-Centric Architecture for Low-Latency 1M Context Attention Servingcited by 0
  7. 2026NELSSA: A GPU-PNM Heterogeneous System for Mixed-Length LLM Serving via Length-based Request Placementcited by 0
  8. 2026NOVA: Technology-Architecture Co-Design of Near-Memory Processing for Attention-SSM-MoE Hybrid LLM Inferencecited by 0
  9. 2026Hot-Cold Tiering of HBM and High Bandwidth Flash for Agentic LLM Servingcited by 0
  10. 2026Characterizing High Bandwidth Flash for LLM Servingcited by 0