Nvidia not cutting it? Google and Amazon’s latest AI chips have arrived
Cloud-based AI training got a little more diverse this week after Amazon Web Services and Google Cloud announced the general availability of their latest custom AI accelerators.
Amazon claims the instances are between 40 percent and 250 percent higher performance in BF16 and 32-bit TensorFlow workloads than its Nvidia A100-powered P4d instances, according to Amazon's internal benchmarks. The accelerator also supports FP32, FP16, UINT8, and a configurable FP8 datatype. FP8 hasThe instances are available in two sizes: Amazon's trn1.2xlarge pairs eight vCPUs with a single Trainium chip, 64GB of memory divided evenly between the CPU and accelerator, 12.
The accelerator uses the same Neuron SDK as Amazon's previously announced Inferentia inferencing chip, which comes with a compiler, framework extensions, a runtime library, and developer tools. Put together, Amazon claims workloads written in popular ML frameworks, such as PyTorch and TensorFlow, can be adapted to run on Trainium with minimal refactoring.
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