Sycomp Achieves Second Data-to-GPU Performance on Google Cloud for AI Scientific Discovery

Sycomp A Technology Company, Inc., a leader in high-performance computing (HPC) and data storage solutions, has announced a groundbreaking achievement in Artificial Intelligence (AI) and scientific discovery.
The company has reached 1.2 TB per second of data-to-GPU performance on Google Cloud (GCP), powering a range of data-intensive AI workloads including Gen AI, Agentic AI, Computer Vision, Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP).
Setting New Standards in HPC and AI Workloads
This milestone was accomplished using the Sycomp Intelligent Data Storage Platform, designed specifically for high-performance computing and data-intensive AI research.
By leveraging Sycomp's Real Insight Storage Engine (RISE), in combination with Google Cloud's infrastructure, Sycomp has achieved unprecedented speed and efficiencyfor AI applications, helping researchers and enterprises push the boundaries of AI capabilities.
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Google’s Role in the Achievement
Dean Hildebrand, Technical Director at Google Cloud, said, “GCP's HPC and AI/ML customers demand amazing performance at competitive prices.”
He added, “By scaling to 1.2 TB/s of low latency reads and dynamically accessing and synchronizing data with existing Google Cloud Storage buckets, the latest Sycomp offering in the GCP Marketplace delivers a differentiated high-performance storage offering that can support the most critical and demanding workloads."
The Sycomp Intelligent Data Storage Platform boosts GKE performance, delivers high GPU utilization (97%) with over 29 GB/sec throughput, and enables seamless data mobility across environments. With 1.2 TB/sec I/O throughput and optimized cost-performance, it powers large-scale AI workloads efficiently.
Sycomp, with over 30 years of experience in data center, HPC, and storage solutions, has positioned itself as a leader in delivering AI infrastructure, advanced AI technology design, and development services.