MGPU-TSM: A Multi-GPU System with Truly Shared Memory

Understand

The sizes of GPU applications are rapidly growing.

• They are exhausting the compute and memory resources of a single GPU, and are demanding the move to multiple GPUs.
• However, the performance of these applications scales sub-linearly with GPU count because of the overhead of data movement across multiple GPUs.
• Moreover, a lack of hardware support for coherency exacerbates the problem because a programmer must either replicate the data across GPUs or fetch the remote data using high-overhead off-chip links.