Rommie E. Amaro
ABSTRACT
Voyager is an innovative computational resource designed by the San Diego Supercomputer Center in collaboration with technology partners to accelerate the development and performance of artificial intelligence and machine learning applications in science and engineering. Based on Intel’s Habana Labs first-generation deep learning (Gaudi) training and (Goya) inference processors, Voyager is funded by the National Science Foundation’s Advanced Computing Systems & Services Program as a Category II system and will be operated for 5 years, starting with an initial 3-year exploratory test-bed phase that will be followed by a 2-year allocated production phase for the national research community. Its AI-focused hardware features several innovative components, including fully-programmable tensor processing cores, high-bandwidth memory, and integrated, on-chip RDMA over Converged Ethernet network interfaces. In addition, Habana’s SynapseAI software suite provides seamless integration to popular machine learning frameworks like PyTorch and TensorFlow for end users. Here, we describe the design motivation for Voyager, its system architecture, software and user environment, initial benchmarking results, and the early science use cases and applications currently being ported to and deployed on the system.
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Index Terms
- Voyager – An Innovative Computational Resource for Artificial Intelligence & Machine Learning Applications in Science and Engineering
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