Amazon Web Services began offering P3 instances, the next generation of Amazon Elastic Compute Cloud (Amazon EC2) GPU instances for compute-intensive applications that require massive parallel floating point performance, including machine learning, computational fluid dynamics, computational finance, seismic analysis, molecular modeling, genomics, and autonomous vehicle systems. The instances are based on NVIDIA Tesla V100 GPUs.
AWS said the new P3 instances allow customers to build and deploy advanced applications with up to 14 times better performance than previous-generation Amazon EC2 GPU compute instances, and reduce training of machine learning applications from days to hours.
P3 instances can combine up to eight NVIDIA Tesla V100 GPUs to provide up to one petaflop of mixed-precision, 125 teraflops of single-precision, and 62 teraflops of double-precision floating point performance. A 300 GB/s second-generation NVIDIA NVLink interconnect enables high-speed, low-latency GPU-to-GPU communication. P3 instances also feature up to 64 vCPUs based on custom Intel Xeon E5 (Broadwell) processors, 488 GB of DRAM, and 25 Gbps of dedicated aggregate network bandwidth using the Elastic Network Adapter (ENA).
“When we launched our P2 instances last year, we couldn’t believe how quickly people adopted them,” said Matt Garman, Vice President of Amazon EC2. “Most of the machine learning in the cloud today is done on P2 instances, yet customers continue to be hungry for more powerful instances. By offering up to 14 times better performance than P2 instances, P3 instances will significantly reduce the time involved in training machine learning models, providing agility for developers to experiment, and optimizing machine learning without requiring large investments in on-premises GPU clusters. In addition, high performance computing applications will benefit from up to 2.7 times improvement in double-precision floating point performance.”
