Power topologies: Balancing cost, speed, efficiency, and isolation. Data centers—specifically those driving the latest innovations in AI—are consuming more and more power.

AI workloads have fundamentally transformed data center communication requirements, introducing unprecedented demands for ...

The statistics are undeniable, unavoidable, and frankly staggering. The International Energy Agency’s October report found ...

AWS’s Project Rainier is building one of the world’s largest AI supercomputing clusters, powered by custom Trainium2 ...

Explore how 800G OSFP DR8 optical transceivers are revolutionizing data center performance. Learn about their technical ...

The new Cadence LPDDR6/5X memory IP is a key enabler for scaling up the AI infrastructure to accommodate growing memory ...

AMAX Deploys NVIDIA DGX SuperPODTM with NVIDIA DGXTM B200 Systems The deployment will deliver a massive 4.6 exaflops of AI training, backed ...

AI requires a lot of data, particularly for training models. The problem is that planar chips are unable to process all that data quickly and efficiently due to reticle limitations, which is why many ...

From collaborative robots, embedded computing, controllers, linear guides and panel PCs to Time-Sensitive Networking switches ...

The DS925+ comes with one of its two SO-DIMM slots populated with 4GB of DDR4 ECC RAM. You can upgrade to two sticks of Synology’s own 16GB ECC RAM (for 32GB total) if required, but not if you’re ...