San Francisco, CA — MLCommons has announced results for its MLPerf Storage v2.0 benchmark suite, designed to measure the performance of storage systems for machine learning workloads in an architecture-neutral, representative, and reproducible manner. According to MLCommons, the results show that storage systems performance ….
DDN Touts MLPerf Storage Benchmark Performance
Chatsworth, Calif. — August 4, 2025 — DDN announced it has set a new benchmark for performance and efficiency with its AI400X3 storage appliance in the latest MLPerf Storage v2.0 benchmarks. Powered by DDN’s EXAScaler parallel file system, the AI400X3 is engineered to accelerate AI workloads. For large enterprises, this means faster time-to-insight, lower operational costs, […]
Phison and Supermicro Collaborate on Storage for AI and Hyperscale Workloads
SAN JOSE – August 5, 2025 – Phison Electronics (8299TT), a provider of NAND flash controllers and storage solutions, is collaborating on server solutions with Supermicro for high-density workloads. Customers using Supermicro’s Petascale Storage Family will be able to leverage Phison’s 122.88 TB Pascari D205V SSD, featuring an E3.L form factor and Gen5 NVMe performance. […]
At ISC 2025: Goethe University Discusses AI-Powered Scientific Research on the VDURA Data Platform
At last week’s ISC 2025 conference in Hamburg, we spoke with Prof. Volker Lindenstruth, Director of the Center for Scientific Computing at Goethe University, Frankfurt. Researchers ….
News Bytes 20250421: Chips and Geopolitical Chess, Intel and FPGAs, Cool Storage, 2nm CPUs in Taiwan and Arizona
Good April morning to you! It’s been an active week in the world of HPC-AI, here’s a quick (8:43) rundown of recent industry news: Nvidia, AMD and China export rules, Intel sells part of FPGA business, storage investments soar, 2nm coming to Taiwan and Arizona
Generative AI’s Accuracy Depends on an Enterprise Storage-driven RAG Architecture
[SPONSORED POST] In this sponsored article, Eric Herzog, CMO of Infinidat, suggests that as part of a transformative effort to bring one’s company into the AI-enhanced future, it’s an opportunity to leverage intelligent automation with RAG to create better ….
Innovations in the Pure Storage Platform Help Customers Keep Pace with AI’s Rapid Evolution
Pure Storage® (NYSE:PSTG), the IT pioneer that delivers advanced data storage technologies and services, announced new capabilities in the Pure Storage platform that are changing the game for how IT and business leaders can radically improve their ability to deploy AI, improve cyber resilience, and modernize their applications.
Keep it Simple, Storage
In this contributed article, Jordan Winkelman, Quantum’s Field CTO, discusses how organizations across industries are facing a shift in infrastructure and storage requirements to deliver incredible performance, flexibility, and scalability on a level we’ve never seen before because of the proliferation of AI technologies. Moving forward, there will be a major focus on simplicity in storage—often through the use of AI—to keep up with changing demands, allowing organizations to maximize AI to give them a competitive advantage.
DDN AI400X2 Turbo Appliance Accelerates Gen AI and Inference for Data Center and Cloud by 10x
DDN®, a global leader in artificial intelligence (AI) and multi-cloud data management solutions, announced the latest addition to its powerful A3I® solutions, the DDN AI400X2 Turbo. 30% more powerful than the AI400X2, the previous industry performance leader, the AI400X2 Turbo boasts faster performance and expanded connectivity options.
Pure Storage Accelerates Enterprise AI Adoption to Meet Growing Demands with NVIDIA AI
Pure Storage® (NYSE: PSTG), the IT pioneer that delivers advanced data storage technology and services, today announced new validated reference architectures for running generative AI use cases, including a new NVIDIA OVX-ready validated reference architecture. As a leader in AI, Pure Storage, in collaboration with NVIDIA, is arming global customers with a proven framework to manage the high-performance data and compute requirements they need to drive successful AI deployments.











