H3 Platform Official Website

Sep 07, 2026 182

The Memory Wall in GNNs and Vector Databases—and How NVIDIA SCADA Addresses It

Large GNN and graph-based vector-search workloads can encounter a memory wall as datasets exceed local GPU HBM capacity and irregular access patterns make data harder to retrieve efficiently. NVIDIA® SCADA™ addresses the storage-access layer by enabling GPU-initiated, high-IOPS access to small blocks of data on NVMe, allowing HBM to serve performance-sensitive working data while NVMe provides a larger, cost-effective capacity tier. Falcon 6048 supports this GPU-to-storage data path by integrating GPU resources, high-density NVMe storage, and PCIe Gen6 connectivity in a converged system architecture that works with NVIDIA SCADA.

GPU-Accelerated Storage

Aug 28, 2026 417

What Is NVIDIA SCADA? From CPU-Centric I/O to GPU-Initiated Access Across Multiple NVMe SSDs

NVIDIA® SCADA™ is a GPU-oriented storage I/O architecture that enables GPU threads to initiate and control fine-grained NVMe operations, reducing CPU involvement within the SCADA I/O path. By distributing concurrent requests across multiple SSDs, systems can access greater aggregate capacity and parallel I/O resources for datasets beyond local GPU memory. SCADA does not replace HBM or eliminate the host CPU, and realized performance depends on workload and system configuration. Falcon 6048 integrates GPUs, Broadcom PCIe Gen6 switching, host management, and up to 48 E1.S NVMe SSDs for solutions that work with NVIDIA® SCADA™.

GPU-Accelerated Storage

Apr 08, 2026 1064

GPU-Accelerated Storage Fundamentals #1 — Why AI Needs a New Kind of Storage-- Extremely High Input-Output Per Second Storage

Modern AI workloads shift storage demands from bandwidth to high IOPS and concurrency. GPUs require continuous small, random data access (512B–8KB), making data delivery—not compute—the main bottleneck. Traditional CPU-centric storage cannot sustain the required parallelism, leading to underutilized GPUs. As a result, storage must evolve from capacity-focused (TB/TCO) to concurrency-driven (IOPS/TCO), becoming an active, high-performance data layer for AI systems.

AI Storage

Dec 03, 2025 6485

AI Storage Fundamentals #1 — Why AI Needs a New Kind of Memory/Storage

AI now bottlenecks on storage, not compute. GPUs demand fast, parallel, low-latency data delivery.

CXL

Oct 16, 2025 3760

Supercharging Your Server Efficiency? CXL Memory Sharing Might Be the Answer

Unlock stranded memory and redefine data center efficiency with H3’s CXL Memory Sharing—delivering scalable, high-performance, and composable infrastructure for next-gen AI and HPC workloads.

GPU

May 18, 2025 270204

Which GPU Is The Best? RTX 5090, RTX PRO 6000 Blackwell, or RTX 4090?

Compare RTX 5090, RTX PRO 6000 Blackwell, RTX 4090, and RTX 6000 Ada performance in deep learning, rendering, and gaming to figure out the best value GPU in different fields.

GPU

Oct 20, 2022 2026

Toward PCIe Gen 5 Composable Infrastructure as a Service

H3 appreciates the opportunity to present at Panel session @SC22. PCIe Gen 5 series will also be launched in the event.

GPU

Jul 25, 2022 14599

CXL 2.0 - GPU Memory Sharing and Expansion

Discuss the possibility to expand GPU memory with the emerging CXL interconnect technology.

Composable Infrastructure

Jun 10, 2022 3583

Cost-efficient Composable Infrastructure - Software, Physical, or Mixed Composable?

Explore the benefit of hardware and software integrated composable approach and how it address the emerging demand on composable infrastructure.

NVMe SSD

Jun 06, 2022 5427

Future Datacenter Storage - NVMe Over PCIe Fabric

PCIe, as a fabric, has several natural strength concerning NVMe applications. PCIe network eliminates transport abstraction between host and the NVMe SSD as NVMe protocol transfer data via PCIe Bus directly. Moreover, the high-bandwidth and low-latency that PCIe offers reduces bottleneck caused by networking.

GPU

Mar 25, 2022 7615

Big Accelerator Memory-Enhancing GPU and Storage Efficiency with PCIe Expansion Solution

Explore big accelerator memory (BaM) architecture and the benefit it brings to GPU accelerated applications.

GPU

Jan 25, 2022 3058

Composable Infrastructure - Composable API Framework

get ready for next generation IT infrastructure with composable API.

Tag: AI

The Memory Wall in GNNs and Vector Databases—and How NVIDIA SCADA Addresses It

What Is NVIDIA SCADA? From CPU-Centric I/O to GPU-Initiated Access Across Multiple NVMe SSDs

GPU-Accelerated Storage Fundamentals #1 — Why AI Needs a New Kind of Storage-- Extremely High Input-Output Per Second Storage

AI Storage Fundamentals #1 — Why AI Needs a New Kind of Memory/Storage

Supercharging Your Server Efficiency? CXL Memory Sharing Might Be the Answer

Which GPU Is The Best? RTX 5090, RTX PRO 6000 Blackwell, or RTX 4090?

Toward PCIe Gen 5 Composable Infrastructure as a Service

CXL 2.0 - GPU Memory Sharing and Expansion

Cost-efficient Composable Infrastructure - Software, Physical, or Mixed Composable?

Future Datacenter Storage - NVMe Over PCIe Fabric

Big Accelerator Memory-Enhancing GPU and Storage Efficiency with PCIe Expansion Solution

Composable Infrastructure - Composable API Framework