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Cloud Deep Learning Chips Training & Inference
This document summarizes various chips for deep learning training and inference in the cloud from companies such as Google, Intel, Habana Labs, Alibaba, and Graphcore. It provides information on the specs and capabilities of each chip, such as the memory type and TFLOPS, and links to product pages and documentation. It also discusses collaborations between companies on projects like Glow, ONNX, and OCP accelerator modules.
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Cloud Deep Learning Chips Training & Inference
- 1. Cloud Deep LearningChips Training & Inference Created date：2019.12.07 Updated date : 2019.12.15/17/25 ＠Vengineer
- 2. This is asummary of learning and inference chips for deep learning in the cloud. Each company's chips, product photos and images are borrowed from the URL on the same page.
- 3. Habana Labs：Goya (DRAM) IntelNervana：NNP-I (DRAM) Google：TPU v1 (SRAM) Groq (SRAM) Alibaba：Hanguang(含光) 800 (SRAM) The inference chip does not have an interconnect itself. InferenceTraining Google：TPU v2/v3 (HBM2) Intel Nervana：NNP-T (HBM2) Habana Labs：Gaudi (HBM2) Alphaics：RAP (HBM2 option) Huawei：Ascend 910 (HBM2) Graphcore：GC2 (SRAM) Cerebras：CS-1 (SRAM) The training chip has its own interconnect. https://vengineer.hatenablog.com/entry/2019/11/05/060000 https://github.com/basicmi/AI-Chip https://twitter.com/jwangARK/status/1189560904872058880
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- 5. Google Cloud TPUv2/v3 https://cloud.google.com/tpu/docs/system-architecture Cloud TPU v2 180 TFLOPS 64 GB HBM Cloud TPU v3 420 TFLOPS 128 GB HBM
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- 7. Habana Gaudi https://habana.ai/ 2019.12.17(16): Intel が 2Bドル(約2200憶円)で買収
- 8. Alphaics：Real AI Processing(RAP) https://www.alphaics.ai/
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- 10. Enflame Technology：邃思 DTU http://www.enflame-tech.com/products.html CloudBlazer PCIeGen4 x16 HBM2 16GB (512GB/s) T10：PCIe Card (255W) FP32 ：20TFLOPS FP16/BF16：80TFLOPS T11：OAM (300W FP32 ：22TFLOPS FP16/BF16：86TFLOPS
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- 17. Habana Goya 2019.12.17(16): Intel が 2Bドル(約2200憶円)で買収 https://habana.ai/ Glow https://github.com/pytorch/glow
- 18. groq：Tensor Streaming Architecture(TSA) https://groq.com/ https://groq.com/groq-announces-worlds-first-architecture-capable-of-petaops-on-a-single-chip/ https://www.electronicdesign.com/industrial-automation/groq-s-ai-accelerator-eyes-hyperscalers-auto nomous-vehicles
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- 21. Glow: A community-drivenapproach to AI infrastructure specification https://engineering.fb.com/ml-applications/glow-a-community-driven-approach-to-ai-infrastructure/ https://github.com/pytorch/glow
- 22. Intel and BaiduContinue Collaboration across AI, AD and 5G https://newsroom.intel.com/articles/intel-baidu-continue-collaboration-across-ai-ad-5g/ ● BaiduBrain* (Baidu’s AI platform), ● PaddlePaddle* (Baidu’s deep learning platform) ● DuerOS* (Baidu’s AI-powered voice assistant platform) ● Apollo* (Baidu’s autonomous driving platform) ● Intel® Xeon® Scalable platform ● Intel® Optane™ DC Persistent Memory ● Intel® Optane™ DC SSD ● silicon photonics ● Ethernet ● Intel AI accelerators and Intel software stack
- 23. Training PyTorch modelson Cloud TPU Pods https://cloud.google.com/tpu/docs/tutorials/pytorch-pod github : https://github.com/pytorch/xla
- 24. MICROSOFT AND GRAPHCORE COLLABORATETO ACCELERATE ARTIFICIAL INTELLIGENCE https://www.graphcore.ai/posts/microsoft-and-graphcore-collaborate-to-accelerate-artificial-intellig ence Today we are very excited to share details of our collaboration with Microsoft, announcing preview of Graphcore® Intelligence Processing Units (IPUs) on Microsoft Azure. ● Graphcore IPUs with Dell EMC DSS 8440 Server ● Graphcore also delivers a full training runtime for ONNX and is working closely with the ONNX organisation to include this in the ONNX standard environment. Initial PyTorch support is available in Q4 2019 with full advanced feature support becoming available in early 2020.
- 25. Baidu, Facebook andMicrosoft work together to define the OCP Accelerator Module specification https://www.opencompute.org/blog/baidu-facebook-and-microsoft-work-together-to-define-the-oc p-accelerator-module-specification https://146a55aca6f00848c565-a7635525d40ac1c70300198708936b4e.ssl.cf1.rackcdn.com/images/22fa829b159a4c ea7b33aa12bc2c61909e52d077.pdf Other than Apple and Amazon =>
- 26. I am acomputer engineer, not a deep learning craftsman ありがとうございました。 Thanks ＠Vengineer ソースコード解析職人 Source code analysis craftsman