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Meta Plans Four New MTIA Generations

Meta Plans Four New MTIA Generations
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#ai-chips#custom-silicon#hardware-strategymtiametamtia

💡Meta's 4 new AI chips in 2 yrs accelerate custom silicon for AI infra

⚡ 30-Second TL;DR

What Changed

MTIA custom silicon central to Meta's AI infrastructure

Why It Matters

Meta's push strengthens in-house AI hardware, potentially pressuring Nvidia dominance and spurring efficiency gains. AI practitioners gain insights into scalable custom silicon trends for large-scale deployments.

What To Do Next

Monitor Meta engineering blog for MTIA benchmark releases to evaluate vs. Nvidia GPUs.

Who should care:Developers & AI Engineers

Key Points

  • MTIA custom silicon central to Meta's AI infrastructure
  • Four new MTIA generations planned over next two years
  • Focused on powering Meta's AI workloads

🧠 Deep Insight

Background and context from public sources — not the original article. 6 sources cited.

🔑 Enhanced Key Takeaways

  • First-generation MTIA, announced May 18, 2023, was fabricated on TSMC 7nm process, operates at 800 MHz with 102.4 TOPS INT8 and 25W TDP, targeting recommendation system inference[1][2][3].
  • Next-generation MTIA uses TSMC 5nm process, clocks at 1.35 GHz with 90W TDP, deployed in rack systems holding up to 72 accelerators, achieving 3x performance improvement over v1[4].
  • MTIA development began in 2020, with chips received as early as 2021; features 64 PEs in 8x8 grid, 128 MB on-chip SRAM at 800 GB/s bandwidth, and up to 128 GB LPDDR5 off-chip[1][3].

🛠️ Technical Deep Dive

  • MTIA v1: TSMC 7nm, 800 MHz, 102.4 TOPS INT8 / 51.2 TFLOPS FP16, 25W TDP, 128 MB SRAM (800 GB/s), up to 128 GB LPDDR5 (176 GB/s), 8 PCIe 4.0 lanes, 64 PEs in 8x8 mesh[1][2][3].
  • Architecture: 64 Processing Elements (PEs) each with 128 KB local SRAM, supports TLP/DLP/ILP/MLP, mesh network for inter-PE and memory connectivity[3].
  • Next-gen (v2): TSMC 5nm, 1.35 GHz, 90W TDP, 1.12B gates, 373 mm² die area, on-chip 128 MB (800 GB/s), off-chip 64 GB LPDDR5 (176 GB/s), deployed in 72-accelerator racks with 6x throughput gain[4].
  • Deployment: Yosemite V3 servers with 12 accelerators per server using PCIe switches for inter-accelerator communication bypassing host CPU[3].

🔮 Future ImplicationsAI analysis grounded in cited sources

Meta will reduce dependence on Nvidia GPUs for inference by 2028
MTIA is deployed at scale for ads/ranking workloads with efficiency gains over vendor silicon, alongside a training chip ramping up and multiple chips in development[6].
Four new MTIA generations will enable denser AI clusters by 2028
Next-gen already supports 72 accelerators per rack at higher clock/power for broader model sizes, aligning with plans for multiple chips and Hyperion 5GW cluster[4][6].

Timeline

2020-01
MTIA development initiated for internal AI workloads
2021-08
First MTIA chips fabricated on TSMC 7nm and received by Meta
2023-05
MTIA v1 publicly announced at AI Infra @ Scale event
2023-06
MTIA v1 paper presented at ISCA conference
2024-01
Next-generation MTIA v2 first silicon to production in under 9 months
2025-09
MTIA confirmed deployed at scale for ads workloads with training chip ramping

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Original source: Meta Newsroom

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