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Home » Applications » GPUs and AI Accelerators

GPUs and AI Accelerators

Home » Applications » GPUs and AI Accelerators

GPUs and AI Accelerators

Enabling Complex Topologies for Emerging AI/ML Applications

The proliferation of applications for artificial intelligence (AI) has spurred the creation of dedicated hardware platforms like GPU-based accelerator trays or purpose-built semiconductor clusters for machine learning and neural network training.

​Machine learning (ML) accelerators need reliable, high-bandwidth, and low-latency connectivity with maximum up-time to keep pace with the influx of data needing to be processed.

AI Computing System Block Diagram

RT = Retimer

Requirements & Challenges

  • Passing through multiple connectors between CPU — Retimer — Switch — GPU at PCIe® 4.0 and PCIe 5.0 speeds causes more reflections and insertion loss​
  • Complex topology with multiple links and separate clocking segments​

Aries Retimer Benefits

  • Supports PCIe reach extension >36 dB on both Tx & Rx with best-in-class SerDes​
  • Offers high robustness by passing intensive interoperability tests with Broadcom and Microsemi switches
  • Extensive interop testing with GPU and dedicated inference / learning AIC vendors
  • Supports separate reference clock to accommodate PCIe interconnect​ without needing to send REFCLK across the midplane

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Aries Smart Retimers
  Product Brief
Astera Labs PCIe® 4.0, PCIe 5.0, and CXL™ x16 and x8 Low-Latency Smart Retimers

PCIe 5.0

x 8
x 16

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