ILPG: A Parallel Architecture for Distributed Large Language Model Processing
Year: 2026
Type: article
Abstract: This work introduces ILPG, a proposed architecture for large language model (LLM) computation that explores parallel reasoning structures instead of strictly sequential token generation as used in transformer-based models.The approach investigates how AI workloads could be partitioned and executed in parallel across distributed computational resources, including idle devices and underutilized memory available across billions of connected systems worldwide.If validated at scale, this architecture could enable a new model of AI infrastructure that is less dependent on centralized data centers and more capable of leveraging globally distributed computational capacity.The research presents the conceptual framework, experimental exploration, and early evaluation of latency, coherence, and computational efficiency improvements compared to traditional sequential pipelines.
Author: Aquino, Rafael
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7137109656
FWCI:
Cites:
Cited by:
Related to: