Break Through Your AI Memory Scaling Limitations
Overcome traditional computational limitations and get unprecedented performance, scalability, and cost-effectiveness with Compute Express Link® (CXL) memory expansion and pooling technology.
Large AI Model Training
Memory Pain Points
The widening performance gap between processors and memory—known as the "memory wall"—is a particularly significant challenge for memory-intensive applications such as training large artificial intelligence (AI) models requiring ultra-fast memory bandwidth which cannot keep up with the increasing compute processing demand.
Slow Data Transfer
The time it takes to move data between the GPU and memory (or across multiple GPUs) can create significant bottlenecks that lengthen training time.
Inference Latency
For AI inference that uses trained models, the memory wall can increase latency as the AI model accesses data from memory to make its predictions.
Reduced Throughput
If the memory system cannot keep up with the processing demands of inference requests, the overall throughput of the AI system will decline.
Scalability Challenges
Scaling AI models to serve a large number of users can run up against memory limitations, requiring more hardware and complex infrastructure to resolve.
Scale the AI Memory Wall & Resolve Bottleneck Limits With CXL® Technology
Seeing processors becoming faster at executing instructions much more quickly than memory can supply the data they need, industry leaders such as Alibaba, Cisco, Dell EMC, Facebook, Google, Hewlett Packard Enterprise, Intel Corporation, and Microsoft teamed up with SMART Modular Technologies to develop technical specifications that can facilitate breakthrough performance for emerging usage models while also supporting an open ecosystem for data center accelerators and other high-speed enhancements in order to address the performance bottleneck.
What is CXL Technology?
CXL is an industry open standard protocol that redefines how servers manage memory and compute resources. By enabling high-speed, low-latency connections between central processing units (CPUs) or graphics processing units (GPUs) and memory, CXL eliminates traditional data processing bottlenecks and unlocks new levels of scalability and performance for data-intensive workloads which are increasingly used in emerging applications powered by AI.
Speed and accuracy drive competitive advantage. For organizations that require competitive insights faster, CXL delivers game-changing benefits:
• Faster data processing: Real-time analysis of massive datasets with minimal delay.
• Improved infrastructure efficiency: Optimized resource utilization and lower operational costs.
• Scalable, future-proof solutions: Seamlessly expandable memory to meet evolving data demands without costly infrastructure overhauls.
CXL Enables Lower Cost Scaling of Memory Capacity
The new family of Add-In Cards (AICs) from Penguin Solutions are the first high-density dual in-line memory module (DIMM) AICs to adopt the CXL protocol. Our 4-DIMM and 8-DIMM products support industry-standard DDR5 DIMMs and allow server and data center architects to add up to 4TB of memory quickly using a familiar, easy-to-deploy form factor.
With our new AICs, servers can reach up to 1TB of memory per CPU using cost-effective 64GB RDIMMs. They also offer an opportunity for supply chain optionality; depending on market conditions, replace high-density RDIMMs with a larger number of lower density modules to reduce system memory costs without compromising on compute power or AI system performance.
Keep Up With Advances in Accelerated Computing Workloads
With AI, high-performance computing (HPC), and machine learning (ML) requiring large amounts of high-speed memory that exceeds what conventional servers can accommodate, attempts to add more system memory via the traditional DIMM-based parallel bus interface is problematic due to pin limitations on CPUs.
CXL-based solutions are more pin-efficient which means more available possibilities for adding memory. Our 4-DIMM and 8-DIMM AICs leverage this technology with advanced CXL controllers that eliminate memory bandwidth bottlenecks and capacity constraints for compute-intensive AI, HPC, and ML workloads.
Reach out to Penguin Solutions today to learn more about our CXL products and explore how we can help you affordably scale the memory wall, unleash your AI initiatives, and turn your data into actionable insights faster.
AI 記憶體牆是指 CPU 和加速器的處理速度超過可用的記憶體頻寬和容量時所產生的效能瓶頸。這種瓶頸限制了可以有效率地訓練和部署的 AI 模型的規模和複雜性。
擴展 AI 記憶體牆需要提高記憶體和處理器之間的資料傳輸效率，以減少延遲並消除運算密集型工作（例如 AI 模型訓練）中的瓶頸。
AI 訓練和推論涉及處理大量資料集，而記憶體存取延遲可能會限制輸送量並降低效能，尤其是對於大規模的深度學習模型。
隨著 AI 模型的規模和複雜性不斷增長，使用可擴展記憶體解決方案（例如 CXL 技術）的策略對於保持培訓和推論時間可管理且具有成本效益的至關重要。
CXL 透過 CXL 連接記憶體增加記憶體容量和頻寬來解決記憶體牆，讓處理器能夠比處理速度更快地存取資料。它通過為共用記憶體池提供一致、低延遲存取，並利用高速 PCIe 互連，來實現這一目標。
Talk to the Experts at Penguin Solutions
Reach out today and learn how we can help you maximize your memory expansion and pooling capabilities with lower-cost memory capacity scaling using CXL technology.