While it's possible to use third-party monitoring tools with dstack, it is often more convenient to debug your run and
track metrics out of the box. That's why, with the latest release, dstack introduced dstack stats, a new CLI (and API)
for monitoring container metrics, including GPU usage for NVIDIA, AMD, and other accelerators.
At dstack, we've been adding support for AMD GPUs with SSH fleets,
so we saw this as a great chance to test our integration by benchmarking AMD GPUs. Our friends at
Hot Aisle , who build top-tier
bare metal compute for AMD GPUs, kindly provided the hardware for the benchmark.
While dstack helps streamline the orchestration of containers for AI, its primary goal is to offer vendor independence
and portability, ensuring compatibility across different hardware and cloud providers.
Inspired by the recent MI300X benchmarks, we are pleased to announce that RunPod is the first cloud provider to offer
AMD GPUs through dstack, with support for other cloud providers and on-prem servers to follow.