RNGD for high performance AI inference of LLMs
RNGD running on Ampere delivers high-performance LLM and multimodal deployment capabilities while maintaining a very low power profile.
RNGD running on Ampere delivers high-performance LLM and multimodal deployment capabilities while maintaining a very low power profile.
Simplify your enterprise AI journey with trusted open source. Discover Ubuntu optimized for AI on Ampere.
Small form factor Micro ATX motherboards by ASRock Rack for edge AI, CDNs, portable computers, high-end embedded, powerful workstations, and cost-optimized systems. Available with dual 10GbE or dual 25GbE SPF28.
The new Ampere servers configured by ASA Computers feature Cloud Native Processors that offers industry-leading core density, server efficiency, and per-rack performance, with up to 192 cores providing the best performance/$ compute for AI inferencing.
Consolidate your transcoding process, accelerate core functionality and integrate multiple production processes into this high-performance server.
Ampere’s inference acceleration engine is fully integrated with Pytorch framework. PyTorch models and software written with PyTorch API can run as-is, without any modifications.
Ampere’s inference acceleration engine is fully integrated with Pytorch framework. PyTorch models and software written with PyTorch API can run as-is, without any modifications.
Ampere’s inference acceleration engine is fully integrated with ONNX Runtime framework. ONNX models and software written with ONNX Runtime API can run as-is, without any modifications.
Ampere® Processors, with high performance Ampere Optimized Frameworks in Docker images, offer the best-in-class Artificial Intelligence inference performance for standard frameworks including TensorFlow, PyTorch and ONNXRT and llama.cpp. Ampere optimized containers come fully integrated with their respective frameworks.
Ampere instances on OCI are some of the most cost-effective instances available in the Cloud today. OCI Ampere A1 started this with extremely high-performance shapes that with the ability to use the OCI Flex Shapes feature to provision at the single core resolution making this infrastructure very efficient.