---
res:
  bibo_abstract:
  - 'This paper presents a holistic, cross-stack vision for efficient and scalable
    generative AI, motivated by the view that efficiency is most readily improved
    when hardware, compiler, and algorithmic techniques are pursued together rather
    than in isolation. We connect four complementary perspectives: (i) foundational
    hardware innovations, including heterogeneous 2.5D/3D integration and in-memory
    computing, that reduce the compute, memory, and energy footprint of billion- parameter
    models; (ii) extensible compiler infrastructures, built around MLIR, that bridge
    emerging in-memory hardware to real applications and automate design-space exploration;
    (iii) cross-layer and algorithmic techniques –quantization, sparsification, and
    dataflow optimization– that compress and accelerate large language models from
    the cloud to the edge; and (iv) token reduction methods, such as token merging
    and clustering, that attack the quadratic cost of the transformer attention mechanism
    at the model level. By integrating hardware, compiler, and algorithm viewpoints
    into a single narrative, we outline how co-designed solutions across the stack
    can compound to enable affordable, scalable, and democratized access to generative
    intelligence.@eng'
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Weitian
      foaf_name: Wang, Weitian
      foaf_surname: Wang
  - foaf_Person:
      foaf_givenName: Dhingra
      foaf_name: Pratyush, Dhingra
      foaf_surname: Pratyush
  - foaf_Person:
      foaf_givenName: Asif Ali
      foaf_name: Khan, Asif Ali
      foaf_surname: Khan
  - foaf_Person:
      foaf_givenName: Arkapravo
      foaf_name: Ghosh, Arkapravo
      foaf_surname: Ghosh
  - foaf_Person:
      foaf_givenName: Partha Pratim
      foaf_name: Pande, Partha Pratim
      foaf_surname: Pande
  - foaf_Person:
      foaf_givenName: Jeronimo
      foaf_name: Castrillon, Jeronimo
      foaf_surname: Castrillon
  - foaf_Person:
      foaf_givenName: Priyadarshini
      foaf_name: Panda, Priyadarshini
      foaf_surname: Panda
  - foaf_Person:
      foaf_givenName: Cecilia De La
      foaf_name: Parra, Cecilia De La
      foaf_surname: Parra
  - foaf_Person:
      foaf_givenName: Shubham
      foaf_name: Rai, Shubham
      foaf_surname: Rai
  dct_date: 2026^xs_gYear
  dct_title: A Cross-Stack Approach to Efficient and Scalable Generative AI (Special
    Session Paper)@
...