SK hynix CMM-Ax CXL-PNM Solution for LLM Inference

CXL Memory Expansion design like PCIe slot for ASIC Application Specialized Integrated Circuit to make it alternative accelerator module... someone told me that it's impossible to use CXL for high performance computing accelerations...but not all enterprise really need Nvidia or AMD GPU for general purpose computing...

Cornelis Networks introduced a reference architecture pairing its CN6000 SuperNIC 800 Gbps, supporting both Omni-Path and Ultra Ethernet, with AMD 6th Gen EPYC processors and AMD Instinct MI400 series GPUs. The blueprint targets disaggregated AI inference, large-scale training, and HPC simulation. The bottleneck in large-scale AI has shifted from raw compute to the network connecting it. As clusters grow, interconnect performance increasingly determines training time and inference cost. A validated, OEM-ready architecture built around a leading GPU platform lowers the integration risk for operators standing up AI infrastructure and puts Cornelis directly in the conversation as an alternative in high-performance networking, a category that matters more every day. Cornelis plans to share full architecture details and OEM validation results this fall at the OCP Global Summit and AI Infra Summit, timed alongside AMD's Advancing AI 2026 event. We see open, high-bandwidth interconnect as one of the more strategically important layers of the AI stack, and this advances Cornelis's position in it. More from Cornelis Networks: https://lnkd.in/e2vN9JA7 #AIInfrastructure #HPC

Custom Q8 ROCMFPX Quantization Boosts AMD R9700 Performance by 12.5 Percent 📌 A breakthrough in hardware-specific tuning has unlocked a 12.5% performance boost for the AMD R9700 by utilizing a custom Q8_0_ROCMFPX quantization format. By optimizing kernels specifically for the gfx1201 architecture, this method delivers faster inference and smaller model sizes without sacrificing reasoning quality. This development provides a high-performance roadmap for AI engineers looking to maximize local LLM throughput on next-gen AMD silicon. 🔗 Read more: https://lnkd.in/d94JUbBu #Amd #Radeonr9700 #Rocmfpx #Quantization #Gfx1201

This is the CXL moment the industry has been waiting for – moving from evaluation to real‑world hyperscale deployment. The memory wall has become the defining constraint of AI infrastructure, and Marvell's Structera portfolio offers the most comprehensive answer yet. Structera X memory expansion controllers, co‑developed with leading hyperscalers, bring hardware‑accelerated LZ4 compression (up to 3.64× effective capacity) and support for both DDR4 and DDR5, extending the life of existing memory investments while enabling >6TB of DDR5 or >4TB of DDR4 per controller. Structera A near‑memory accelerators integrate 16 Arm Neoverse V2 cores at 3.2 GHz, 200 GB/s memory bandwidth, and inline XTS‑AES 256‑bit encryption – bringing compute directly to the data and reducing data movement by up to 60×. And Structera S 30260, the 260‑lane PCIe Gen 6 / CXL 3.x switch, connects 16 or 32 CPUs or GPUs to up to 48TB of shared memory with 4TB/s aggregate bandwidth at under 460ns round‑trip latency. The results speak for themselves: in GPU memory‑pooling configurations, inference throughput improves by 4.8× and time‑to‑first‑token drops by 82.7%. This is not incremental – it is a fundamental re‑architecting of how AI infrastructure uses memory.

The future of AI depends not only on advanced silicon, but also on a reliable semiconductor supply chain. As technologies like CXL accelerate the evolution of data centers and memory architectures, sourcing the right components at the right time becomes increasingly important. Looking forward to the continued innovation shaping the semiconductor industry. #AI #Semiconductors #ElectronicComponents #SupplyChain #Technology

CXL adoption is moving from evaluation into real-world deployment across hyperscale environments, and memory capacity and bandwidth have emerged as critical constraints on AI performance and scaling. Marvell offers the industry's most comprehensive CXL portfolio spanning three complementary technologies. Structera X memory expansion, developed in close collaboration with leading hyperscalers, enables larger, more flexible memory pools and extends the value of existing DDR4 investments. Structera A near-memory acceleration brings compute directly to the data, with 16 Arm Neoverse V2 cores and 200 GB/s of memory bandwidth reducing data movement and freeing host cores for other tasks. Structera S CXL switching enables rack-scale memory pooling across up to 48 TB of shared memory, with benchmarks showing up to 4.8x higher inference throughput and an 82.7% reduction in time-to-first-token in GPU configurations. Together, the three form a cohesive architecture for disaggregated, composable memory at hyperscale. Associate Vice President Khurram Malik details the full portfolio and the infrastructure trajectory it is designed to support: https://mrvl.co/4z7SrfE #FMS2026

Arm is making a major strategic pivot: moving from pure IP licensing to delivering complete, in-house data centre silicon with the Arm AGI CPU. As AI workloads shift toward agentic AI—requiring continuous coordination, reasoning, and execution across multiple accelerators—the CPU's role as a system orchestrator has never been more vital. 📌 Key Technical & Industry Takeaways: Unprecedented Density: Built on TSMC's 3nm process with 136 Neoverse V3 cores per CPU, enabling 45,000+ cores per liquid-cooled rack and >2× performance per rack over current x86 systems. Ecosystem Adoption: Meta leads initial deployment, backed by OpenAI, Cloudflare, SAP, SK Telecom, and OCP hardware partners. System-Level Verification Focus: Shifting to vertically integrated silicon alters data centre architecture. Validating tightly coupled CPUs, memory systems, and interconnects demands a risk-based, system-scale verification strategy. As compute density scales, component-level testing alone is no longer sufficient—mastering system-level integration and verification is now the critical path for next-gen AI infrastructure. 🔗 Read the full article: https://lnkd.in/esCAdgF7 #Semiconductors #DataCentre #Arm #AIHardware #SystemVerification #Neoverse #SiliconDesign

Arm is making a major strategic pivot: moving from pure IP licensing to delivering complete, in-house data centre silicon with the Arm AGI CPU. As AI workloads shift toward agentic AI—requiring continuous coordination, reasoning, and execution across multiple accelerators—the CPU's role as a system orchestrator has never been more vital. 📌 Key Technical & Industry Takeaways: Unprecedented Density: Built on TSMC's 3nm process with 136 Neoverse V3 cores per CPU, enabling 45,000+ cores per liquid-cooled rack and >2× performance per rack over current x86 systems. Ecosystem Adoption: Meta leads initial deployment, backed by OpenAI, Cloudflare, SAP, SK Telecom, and OCP hardware partners. System-Level Verification Focus: Shifting to vertically integrated silicon alters data centre architecture. Validating tightly coupled CPUs, memory systems, and interconnects demands a risk-based, system-scale verification strategy. As compute density scales, component-level testing alone is no longer sufficient—mastering system-level integration and verification is now the critical path for next-gen AI infrastructure. 🔗 Read the full article: https://lnkd.in/esCAdgF7 #Semiconductors #DataCentre #Arm #AIHardware #SystemVerification #Neoverse #SiliconDesign

Arm is making a major strategic pivot: moving from pure IP licensing to delivering complete, in-house data centre silicon with the Arm AGI CPU. As AI workloads shift toward agentic AI—requiring continuous coordination, reasoning, and execution across multiple accelerators—the CPU's role as a system orchestrator has never been more vital. 📌 Key Technical & Industry Takeaways: Unprecedented Density: Built on TSMC's 3nm process with 136 Neoverse V3 cores per CPU, enabling 45,000+ cores per liquid-cooled rack and >2× performance per rack over current x86 systems. Ecosystem Adoption: Meta leads initial deployment, backed by OpenAI, Cloudflare, SAP, SK Telecom, and OCP hardware partners. System-Level Verification Focus: Shifting to vertically integrated silicon alters data centre architecture. Validating tightly coupled CPUs, memory systems, and interconnects demands a risk-based, system-scale verification strategy. As compute density scales, component-level testing alone is no longer sufficient—mastering system-level integration and verification is now the critical path for next-gen AI infrastructure. 🔗 Read the full article: https://lnkd.in/emhGCNsX #Semiconductors #DataCentre #Arm #AIHardware #SystemVerification #Neoverse #SiliconDesign

🚀 Chiplet Architecture: The Future of Scalable Chip Design As chip designs become more complex, Chiplet Architecture offers a smarter way to build high-performance systems. 🔹 Break complex SoCs into smaller chiplets 🔹 Mix and match different process technologies 🔹 Improve scalability and manufacturing yield 🔹 Enable advanced 2.5D/3D packaging 🔹 Accelerate AI, HPC, automotive & data-center applications Think of chiplets as building blocks for the next generation of semiconductor innovation. 🧩 📞 9217059905 📩 info@jasttech.com 🌐 www.jasttech.com #Chiplet #ChipletArchitecture #Semiconductor #VLSI #AdvancedPackaging #SoC #AIChips #HPC #3DIC #2_5DIC #ChipDesign #JastTech