AI Hardware & Infrastructure

Trillium TPUs

Performance: 4.7x faster than Cloud TPU v5e (BF16 precision)
Scalability: Massive clusters for training, efficient configs for inference
Integration: Optimized for Gemini and next-gen models

Hypercomputer Architecture

Unified Platform: Supports HPC and AI workloads (TPUs, GPUs, CPUs)
Cluster Management: Deploy/manage accelerators as a single unit
Software: Open frameworks, flexible consumption models

TPU v5p

Specs: 8,960 chips/pod, 4,800 Gbps interconnect, 2x FLOPS, 3x HBM vs v4
Advantage: Cost/performance edge over NVIDIA GPUs for large-scale AI

Hardware-Software Co-Design

Optimization: Models and silicon co-developed for max efficiency
Predictable Pricing: Google controls stack, offers stable pricing/availability

[Sources: Google, HPCWire, TechCrunch 2025]

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