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researcher

Axel Acosta

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.AR1
  • cs.DC1
  • cs.LG1

identity via Semantic Scholar / OpenAlex

most citedAn End-to-End HW/SW Co-Design Methodology to Design Efficient Deep Neural Network Systems using Virtual Models

2 citations · 3 across the 2 of their papers we have counts for

collaborators

3 papers

cs.AR2021★ 1 cited

Enabling Cross-Domain Communication: How to Bridge the Gap between AI and HW Engineers

Michael J. Klaiber, Axel J. Acosta, Ingo Feldner +1

A key issue in system design is the lack of communication between hardware, software and domain expert. Recent research work shows progress in automatic HW/SW co-design flows of ne…

cs.DC2021

Joint Program and Layout Transformations to enable Convolutional Operators on Specialized Hardware based on Constraint Programming

Dennis Rieber, Axel Acosta, Holger Fröning

The success of Deep Artificial Neural Networks (DNNs) in many domains created a rich body of research concerned with hardware accelerators for compute-intensive DNN operators. Howe…

cs.LG2019★ 2 cited

An End-to-End HW/SW Co-Design Methodology to Design Efficient Deep Neural Network Systems using Virtual Models

Michael J. Klaiber, Sebastian Vogel, Axel Acosta +5

End-to-end performance estimation and measurement of deep neural network (DNN) systems become more important with increasing complexity of DNN systems consisting of hardware and so…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.