Difference between revisions of "MTIA"
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| − | [[wikipedia:MTIA]] | + | [[wikipedia:MTIA]] [[ASIC]] |
https://ai.facebook.com/blog/meta-training-inference-accelerator-AI-MTIA/ | https://ai.facebook.com/blog/meta-training-inference-accelerator-AI-MTIA/ | ||
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| + | The accelerator is fabricated in TSMC 7nm process and runs at 800 MHz, providing 102.4 [[TOPS]] at [[INT8]] precision and 51.2 [[TFLOPS]] at [[FP16]] precision. It has a thermal design power (TDP) of 25 W. | ||
* [[DLRMs]] | * [[DLRMs]] | ||
| + | * [[PyTorch]] | ||
| − | + | {{Flop}} | |
{{Meta}} | {{Meta}} | ||
{{AI}} | {{AI}} | ||
Latest revision as of 07:12, 21 May 2023
https://ai.facebook.com/blog/meta-training-inference-accelerator-AI-MTIA/
The accelerator is fabricated in TSMC 7nm process and runs at 800 MHz, providing 102.4 TOPS at INT8 precision and 51.2 TFLOPS at FP16 precision. It has a thermal design power (TDP) of 25 W.
FLOP, Exaflop, Teraflop, TFLOP, GFLOP Meta, Metaverse, Meta Quest: 2, 3 Pro, MTIA, LLaMA, Smart Glasses, FAIR, Meta AI
AI: Autonomous driving, OpenAI, Google AI,Eliezer Yudkowsky, DeepMind, Computer Vision, Neural network, Vertex AI, Instadeep, Deep learning, Infogrid, Sapling, AssemblyAI, V7, MTIA, Yann LeCun, AI WiW, Salesforce AI, Pika, Amazon Q, LLM, Ollama, Cloud AI Developer Services, Hugging Face, Databricks
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