SC24: SK hynix Showcasing Advanced Memory Solutions for AI and HPC

At SC24 in Atlanta, GA., SK hynix, Inc. is showcasing its advanced memory solutions for AI and HPC.

This annual event, organized by the Association for Computing Machinery and the IEEE Computer Society since 1988, features the latest developments in HPC, networking, storage, and data analysis.

Returning for its 2nd year, SK hynix is underlining its AI memory leadership through a display of memory products and insightful presentations on AI and HPC technologies. In line with the conference’s ‘HPC Creates’ theme which underscores the impact of supercomputing across various industries, the company is showing how its memory solutions drive progress in diverse fields.

Showcasing advanced memory solutions for AI and HPC

At its booth, the company is demonstrating and displaying a range of products tailored for AI and HPC. The products being demonstrated include its CMM (CXL ⁽¹⁾ Memory Module)-DDR5 ⁽²⁾, AiMX ⁽³⁾ accelerator card, and Niagara 2.0 among others.

The live demonstration of CMM-DDR5 with a server platform featuring Xeon 6 processors shows how CXL memory technology accelerates AI workloads under various usage models. Moreover, visitors to the booth can learn about the latest CMM-DDR5 product with EDSFF ⁽⁴⁾ which offers improvements in TCO ⁽⁵⁾ and performance.

Another live demonstration features AiMX integrated in an ASRock Rack Server to run Meta’s Llama 3 70B, a large language model (LLM) with 70 billion parameters. This demonstration highlights AiMX’s efficiency in processing large datasets while achieving high performance and low power consumption, addressing the computational load challenges posed by attention layers ⁽⁶⁾ in LLMs.

Among the other technologies being demonstrated is Niagara 2.0. The CXL pooled memory solution enables data sharing to minimize GPU memory shortages during AI inference ⁽⁷⁾, making it for LLM models. The company is also demonstrating an HBM with near-memory processing (NMP) ⁽⁸⁾ which accelerates indirect memory access ⁽⁹⁾, a frequent occurrence in HPC. Developed with Los Alamos National Laboratory (LANL), the solution highlights the potential of NMP-enabled HBM to advance next-gen technologies.

Another demonstration is showcasing SK hynix’s updated OCS ⁽¹⁰⁾ solution, which offers significant improvements in analytical performance for real-world HPC workloads compared to the iteration displayed at SC23. Co-developed with LANL, OCS addresses performance issues in traditional HPC systems by enabling storage to independently analyze data, reducing unnecessary data movement and improving resource efficiency. Additionally, the company is demonstrating a checkpoint offloading SSD ⁽¹¹⁾ prototype that improves LLM training resource utilization by enhancing performance and scalability.

In addition to running product demonstrations, SK hynix is also displaying a robust lineup of data center solutions, including its HBM3E ⁽¹²⁾. The 5th–Gen HBM provides high-speed data processing, optimal heat dissipation, and high capacity, making it essential for AI applications. Alongside HBM3E are the company’s rapid DDR5 RDIMM and MCR DIMM products, which are tailored for AI computing in high-performance servers. Enterprise SSDs (eSSDs) including the Gen 5 PS1010 and PEB110 are also on display. Offering ultra-fast RW speeds, these SSD solutions are vital for accelerating AI training and inference in large-scale environments.

Highlighting potential of memory through expert presentations

Jongryool Kim presenting on advancements in memory and storage for HPC and AI systems

During the conference, Jongryool Kim, research director, AI System Infra, presented on Memory & Storage: The Power of HPC/AI, highlighting the memory needs for HPC and AI systems. He focused on 2 key advancements including near-data processing technology using CXL, HBM, and SSDs to improve performance, and CXL pooled memory for better data sharing across systems.

Jeoungahn Park delivering presentation on OCS

Jeoungahn Park, technical leader, sustainable computing team also took to the stage for his talk on Leveraging Open Standardized OCS to Boost HPC Data Analytics. Park explained how OCS enables storage to automatically recognize and analyze data, thereby accelerating data analysis in HPC. He added how OCS enhances resource efficiency and integrates with existing analytics systems, as well as how its analysis performance has been verified in real-world HPC applications.

At SC24, SK hynix is solidifying its status as a pioneer in memory solutions which are driving innovations in AI and HPC technologies. Looking ahead, the company will continue to push technological boundaries with support from its partners to shape the future of AI and HPC.

⁽¹⁾ Compute Express Link (CXL): A PCIe-based next-generation interconnect protocol on which high-performance computing systems are based.
⁽²⁾ CXL Memory Module-DDR5 (CMM-DDR5): A next-gen DDR5 memory module utilizing CXL technology to boost bandwidth and performance for AI, cloud, and high-performance computing.
⁽³⁾ Accelerator-in-Memory Based Accelerator (AiMX): SK hynix’s specialized accelerator card tailored for large language model processing using GDDR6-AiM chips.
⁽⁴⁾ Enterprise and Data Center Standard Form Factor (EDSFF): A collection of SSD form factors specifically used for data center servers.
⁽⁵⁾ Total cost of ownership (TCO): The complete cost of acquiring, operating, and maintaining an asset, including purchase, energy, and maintenance expenses.
⁽⁶⁾Attention layer: A mechanism that enables a model to assess the relevance of input data, prioritizing more important information for processing.
⁽⁷⁾AI inference: The process of using a trained AI model to analyze live data for predictions or task completions.
⁽⁸⁾ Near-memory processing (NMP): A technique that performs computations near data storage, reducing latency and boosting performance in high-bandwidth tasks like AI and HPC.
⁽⁹⁾ Indirect memory access: A computing addressing method in which an instruction providing the address of a memory location that contains the actual address of the desired data or instruction.
⁽¹⁰⁾ Object-based computational storage (OCS): A storage architecture that integrates computation within the storage system, enabling local data processing and minimizing movement to enhance analytical efficiency.
⁽¹¹⁾ Checkpoint offloading SSD: A storage solution that stores intermediate data during AI training, improving efficiency and reducing training time.
⁽¹²⁾ HBM3E: The 5th-gen High Bandwidth Memory (HBM), a high-value, high-performance product that revolutionizes data processing speeds by connecting multiple DRAM chips with through-silicon via (TSV).