Memory Bandwidth
Memory bandwidth refers to the rate at which data can be read from or written to a system's memory by its processors or GPUs. It is typically measured in gigabytes per second (GB/s) and is a critical factor in determining system performance, especially for tasks involving large datasets or high-resolution graphics. High memory bandwidth is essential in applications like video editing, 3D rendering, and scientific computing, where rapid data movement between memory and processors is required to prevent performance bottlenecks.
https://en.wikipedia.org/wiki/Memory_bandwidth
In modern GPUs and processors, advancements in memory bandwidth have been achieved through technologies like GDDR6X and HBM (High Bandwidth Memory). For example, NVIDIA's GeForce RTX 4090 features a memory bandwidth of 1,018 GB/s, made possible by its 384-bit interface and GDDR6X memory. Similarly, HBM2, introduced in 2016, stacks memory chips vertically to shorten data pathways, significantly improving bandwidth. These innovations enable GPUs and processors to handle more data-intensive workloads efficiently.
https://en.wikipedia.org/wiki/High_Bandwidth_Memory
Unified memory architectures, such as those found in Apple Silicon chips, further optimize memory bandwidth by allowing the CPU, GPU, and Neural Engine to share a common pool of memory. This eliminates the need for data duplication and reduces latency, enhancing performance across applications. For instance, the M1 Pro supports 200GB/s of memory bandwidth, enabling seamless multitasking and handling of 4K video and 8K video editing workflows. As technology evolves, increased memory bandwidth will continue to drive improvements in computational and graphical performance.
https://developer.apple.com/documentation/unifiedmemoryarchitecture