AWS 開始推自己的 Machine Learning Chip

除了常見的 GPU 類,以及之前公佈過的 FPGA 外,這次 AWS 推出的是自己做的晶片 AWS Inferentia,以及對應到 EC2 上的機種 inf1:「Amazon EC2 Update – Inf1 Instances with AWS Inferentia Chips for High Performance Cost-Effective Inferencing」。

從介紹可以看到支援的形式:

Each AWS Inferentia chip supports up to 128 TOPS (trillions of operations per second) of performance at low power to enable multiple chips per EC2 instance. AWS Inferentia supports FP16, BF16, and INT8 data types. Furthermore, Inferentia can take a 32-bit trained model and run it at the speed of a 16-bit model using BFloat16.

然後常見的框架都先弄好支援了:

AWS Inferentia comes with the AWS Neuron software development kit (SDK) that enables complex neural net models, created and trained in popular frameworks to be executed using AWS Inferentia based EC2 Inf1 instances. Neuron consists of a compiler, run-time, and profiling tools and is pre-integrated into popular machine learning frameworks including TensorFlow, Pytorch, and MXNet to deliver optimal performance of EC2 Inf1 instances.

現在看起來類似於 Google 弄的 TPU,專為 machine learning 搞出來的 ASIC,等一陣子應該就會有兩者的比較了...

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