Mohamad El-Batal is the Seagate Enterprise Data Solutions (EDS) Chief Technologist, and part of the overall Seagate Office of the CTO team. He is given the opportunity to shape the Seagate EDS strategy and future storage product technology roadmap.In his career Mohamad lead a team... Read More →
Highlight the CXL RAS specific Firmware First error handling use cases that are implemented for the CXL specification which is generic in nature. When developing the support for the CXL RAS Firmware First, encountered different use cases that needs to be solved to implement the firmware and customer problems. The use cases resolution would involve the design and implementation of the firmware to handle them. Usage of primary and secondary Mailbox to overcome the IHV early adoption in engineering/debug effort. Common error signaling protocols usage for protocol errors. GUID and UUID usage in firmware on both CPU/host side, CXL devices and Operating system. Interaction communication failures between the CPU and CXL devices during boot time and run time that needs to be notified to users/operating system. Techniques used to improve the SMI latency. Error pollution use cases handling on both protocol, Memory error firmware notification (MEFN) and Flat2LM cases. The CXL ecosystem comprises of multitude of component vendors like SoC, Memory, Storage, Networking, etc. The explosive growth of internet content and the resulting data storage and computation requirements has resulted in the deployment of heterogenous and complex solutions in the very large-scale data centers. These warehouse sized buildings are packed with server, storage and network hardware. Specifically if there is a uncorrected fatal error detected by hardware that pose a containment risk. The system needs to be reset and restarted if possible to enable continued operation. The error affects the entire CXL device, a persistent/permanent memory device is considered to have experienced a dirty shut-down.
This session will share our practical experience in AI data center architecture planning, covering the critical interplay of computing, storage, and management. We'll delve into our comprehensive approach to designing scalable and efficient AI infrastructure.
A significant portion of our discussion will be dedicated to our innovative storage architecture, which addresses diverse AI workload demands through a dual-part strategy. First, we will present our high-performance storage solution, leveraging BeeGFS and GRAID's cutting-edge technologies with NVMe SSDs to meet the demands of intense AI computation. Second, we will explore our approach to tenant object storage, specifically utilizing GRAID's SupremeRAID alongside NVMe SSDs to provide robust and scalable data management for various user requirements.
The demands of AI training and inference workloads heavily rely on efficient I/O operations. This presentation will explore how SSDs are architected to deliver superior performance across diverse I/O characteristics inherent in these AI processes. We'll demonstrate the advantages of NVMe SSDs in both training and inference environments, highlighting their strengths in handling various I/O patterns. Furthermore, we will delve into the critical aspect of checkpointing performance in AI pipelines, specifically showcasing how FDP significantly enhances checkpointing efficiency by mitigating bandwidth limitations and reducing contention in shared storage systems.
Mohamad El-Batal is the Seagate Enterprise Data Solutions (EDS) Chief Technologist, and part of the overall Seagate Office of the CTO team. He is given the opportunity to shape the Seagate EDS strategy and future storage product technology roadmap.In his career Mohamad lead a team... Read More →
As AI models and data analytics workloads continue to scale, memory bandwidth and capacity have become critical bottlenecks in modern data centers. CXL provides a high-capacity, low-latency memory expansion that can be leveraged in different usage models. CXL memory expansion and Pooling can significantly enhance SQL workload performance and reduced cloud TCO, particularly for in-memory databases and analytics workloads that are bandwidth and capacity constrained. Also Offloading the key-value (KV) cache to Compute Express Link (CXL) memory is emerging as an effective strategy to tackle memory bottlenecks and improve throughput in large language model (LLM) inference serving by storing KV cache, which is critical for efficient autoregressive generation in LLMs.
Mohamad El-Batal is the Seagate Enterprise Data Solutions (EDS) Chief Technologist, and part of the overall Seagate Office of the CTO team. He is given the opportunity to shape the Seagate EDS strategy and future storage product technology roadmap.In his career Mohamad lead a team... Read More →
