FastMediums

FastMediums is a term used to describe a class of data storage and transmission media designed to deliver ultra-low latency and high throughput for modern computing workloads. The concept encompasses a range of technologies that prioritize rapid access and transfer of data, often combining memory-like properties with fast interconnects.

In practice, FastMediums refers not to a single standard but to a family of approaches that aim to reduce access time and bottlenecks in data paths. Typical characteristics include non-volatile or volatile storage with sub-millisecond or sub-microsecond latency, high sustained bandwidth, scalability for large datasets, and energy-efficient operation. Technologies associated with FastMediums include photonic interconnects, 3D-stacked memory, and fast non-volatile memory devices.

The term originated in academic and industry discussions during the 2010s as researchers explored alternatives to traditional hard drives and current DRAM in data centers, AI workloads, and streaming applications. It is used to compare devices and architectures by latency, bandwidth, and integration complexity rather than fixed specifications.

Applications include accelerators for AI training, high-frequency data analytics, real-time streaming, and edge computing where data must be accessed quickly. Proponents highlight the potential for reduced energy per operation and lower tail latency, while critics note ongoing challenges in standardization, cost, and reliability.

FastMediums remains largely conceptual and as a design space rather than a defined technology. It informs discussions about emerging memory systems and interconnects, guiding future research toward faster data movement and storage.