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Liqid Launches the Industry's Most Advanced CXL Memory Pooling Platform for AI and Scientific DiscoveryLiqid® (www.liqid.com), the global leader in software-defined memory and GPU pooling infrastructure, today announced its role as a strategic technology partner in Abaco, the memory-centric computing system designed by Micron, a subcontractor to the U.S. Department of Energy's (DOE) Pacific Northwest National Laboratory (PNNL). Liqid is providing the scale-up memory pool that allows PNNL to expose hundreds of terabytes of coherent active memory to data-intensive AI for Science workloads. Solving the Memory Wall for Scientific AI For decades, memory architectures have limited applications such as computational chemistry, molecular biology, and AI-driven simulation by restricting access to the large memory capacity they require. The Abaco system pioneers CXL-enabled memory pooling and sharing, shattering the capacity limits of individual servers to support massive-scale AI workloads. Liqid delivers the industry's first and only fully disaggregated, software-defined memory pooling solution. In a Liqid rack-scale configuration, up to 160TB of DRAM can be dedicated to a single host or dynamically allocated and shared across as many as 16 server nodes. Real-time allocation of terabytes of memory enables zero stranded capacity and massive performance scaling when needed. What Liqid Contributes to PNNL
Memory Sharing and Benchmark Results Liqid and Micron have also colaborated to enable the industry's first architecture that supports true memory-sharing capabilities. Micron's famfs Linux kernel enhancement enables advanced memory sharing across systems with software cache coherence, laying the foundation for future performance gains through larger shared memory pools, reduced data movement, and more efficient access to massive datasets. With famfs, disaggregated memory pools from the Liqid system become exposed to the host operating system as a file system, requiring no application layer changes to harness the latency and bandwidth advantages of pooled memory. Using the famfs Linux kernel in the Abaco system with Micron high-capacity RDIMMs, Micron lab benchmarks using representative workloads demonstrated performance improvements. Results showed up to 30x faster processing time for graph analytics workloads and up to 7x more tokens per second for certain KV cache workloads, validating the power of CXL memory pooling for AI and scientific computing, with additional optimization and performance gains expected as the platform enables new features. Executive Perspectives "PNNL is exactly the kind of environment that proves what composable CXL memory can do at the frontier of science. PNNL and Micron have built something singular: a memory-centric system designed for the workloads that could define the next decade of AI for Science. Liqid is honored to extend that platform with the scale, orchestration, and composability that turn pooled memory into a programmable resource. This is what tokens per dollar and tokens per watt look like in a national laboratory environment." - Sumit Puri, Founder and CTO, Liqid "PNNL's work demonstrates how CXL-based memory pooling can extend system memory resources beyond the limits of individual servers. By combining Micron high-capacity DRAM with a disaggregated memory architecture, the Abaco system provides researchers with access to larger pools of memory for scientific computing workloads. This project highlights an innovative approach to addressing memory challenges as computing requirements continue to grow." - Vijay Nain, Senior Director of Emerging Memory and Ecosystem Development, Micron Technology "The Abaco system testbed design increases memory capacity by orders of magnitude, which is critical for scientific workloads. We look forward to quantifying that performance improvement in HPC, AI inference, and post-training applications." - James A. Ang, Ph.D., Chief Scientist for Computing, IDSD, Pacific Northwest National Laboratory Why It Matters for AI for Science PNNL will leverage Abaco to advance AI for Science, with AI-integrated computational chemistry as the first user-facing workload. By extending the lab's pooled memory with Liqid's CXL memory fabric, the system can keep larger structures, larger parameter spaces, and heavier intermediate data resident in active memory, directly attacking the memory bottleneck that has historically constrained scientific AI. PNNL's testbed is available to DOE-funded researchers from national laboratories and academia through the Advanced Memory to Support Artificial Intelligence for Science (AMAIS) initiative, funded by the DOE Advanced Scientific Computing Research program within the DOE Office of Science. About Liqid Liqid is the leader in software-defined memory and GPU pooling infrastructure, delivering flexible, high-performance, and efficient on-premises datacenter and edge solutions for next-generation AI inference, KV cache, in-memory databases, VDI, virtualization, and HPC workloads. Liqid solutions are trusted by organizations across financial services, higher education and research, healthcare, telecommunications, media and entertainment, and government and defense. Liqid enables customers to manage, configure, reconfigure, and scale essential compute, accelerators (GPU, DPU, TPU, FPGA), memory, storage, and networking into physical bare-metal server systems in seconds. Liqid customers can optimize their IT infrastructure and achieve up to 100% memory and GPU utilization for maximum tokens per watt, tokens per dollar, and tokens per second. Learn more at www.liqid.com. Copyright © 2026 Liqid, Inc. All Rights Reserved. Liqid and Liqid Matrix are registered trademarks of Liqid, Inc. Other trademarks may be trademarks of their respective owners.
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