The Evolution of High-Speed Interfaces and Memory Systems in AI Architectures

High-speed interfaces and memory systems form the foundation of modern artificial intelligence architectures, enabling them to meet the rapidly growing computational demands of advanced neural networks. Progress in these domains centers on maximizing data movement efficiency while balancing the trade-offs between bandwidth and power consumption. In SerDes design, key considerations include clocking strategies, signal integrity control, and the physical implementation challenges that directly influence overall system performance. Memory hierarchy optimization requires carefully managing capacity, bandwidth, and power efficiency across multiple technology generations. Emerging solutions—such as processing-in-memory architectures and next-generation non-volatile memories—help reduce data transfer overhead. Together, interface design and memory subsystem advancements create the scalable infrastructure needed to power next-generation AI applications across a wide range of deployment environments.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-08-20
DOI
https://doi.org/10.52783/jisem.v10i58s.12638
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

The Evolution of High-Speed Interfaces and Memory Systems in AI Architectures

Phani Paladugu
Journal of Information Systems Engineering & Management
Parallel Computing and Optimization Techniques
article

The Evolution of High-Speed Interfaces and Memory Systems in AI Architectures

Phani Paladugu
article en

Abstract

High-speed interfaces and memory systems form the foundation of modern artificial intelligence architectures, enabling them to meet the rapidly growing computational demands of advanced neural networks. Progress in these domains centers on maximizing data movement efficiency while balancing the trade-offs between bandwidth and power consumption. In SerDes design, key considerations include clocking strategies, signal integrity control, and the physical implementation challenges that directly influence overall system performance. Memory hierarchy optimization requires carefully managing capacity, bandwidth, and power efficiency across multiple technology generations. Emerging solutions—such as processing-in-memory architectures and next-generation non-volatile memories—help reduce data transfer overhead. Together, interface design and memory subsystem advancements create the scalable infrastructure needed to power next-generation AI applications across a wide range of deployment environments.

Journal of Information Systems Engineering & ManagementVol. 10(58s)
Openalex Percentile: Top 76%
Parallel Computing and Optimization Techniques
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The Evolution of High-Speed Interfaces and Memory Systems in AI Architectures — Phani Paladugu · Journal of Information Systems Engineering & Management (2025) | TGRS Research Map | TGRS