Unprecedented AI on CPU Performance with Arm Kleidi
At the heart of all Arm platforms is the Arm CPU. Its ubiquity offers a flexible and energy-efficient target for many AI inference workloads, including deep learning and generative AI. Arm Kleidi, inspired by the Greek word for 'key' focuses on ensuring these workloads get the best out of the underlying Arm Cortex-A or Arm Neoverse CPU.
PyTorch
Arm works closely with the PyTorch community, helping to ensure models running on PyTorch just work on Arm—driving seamless acceleration for even the most demanding AI workloads.
BERT-Large
Arm has been working to improve PyTorch inference performance on Arm CPUs, including optimizing the primary execution modes, Eager Mode and Graph Mode.
Integrating Kleidi improves Llama model inference by up to 18 times, Gemma 2 2B by 15 times, and performance for natural language processing (NLP) models, including 2.2 times uplift on Bert-Large.
Llama 3.1 8B
Using Arm Neoverse V2-based Graviton4 processors, we can achieve an estimated 12 times uplift in token generation rate for a chatbot demo with KleidiAI optimizations applied to PyTorch.
This demo shows how easy it is to build AI applications using LLMs, making use of existing Arm-based compute capacity.
RoBERTa
AWS collaborated with Arm to optimize the PyTorch torch.compile feature for Neoverse V1-based Graviton3 processors with Arm Compute Library (ACL) kernels using oneDNN.
This optimization results in up to 2 times inference performance improvement for the most popular NLP models on Hugging Face.
FunASR Paraformer-Large
FunASR is an advanced open-source automatic speech recognition (ASR) toolkit developed by Alibaba DAMO Academy.
By integrating ACL with PyTorch via oneDNN, we have seen a 2.3 times performance improvement when running the Paraformer model on Neoverse N2-based AliCloud Yitian710 processors.
ExecuTorch
Together, Arm and ExecuTorch, a lightweight ML framework, enable efficient on-device inference capabilities at the edge.
Llama 3.2 1B
Thanks to the collaborative efforts of Arm and Meta, AI developers can now run quantized Llama 3.2 models up to 20% faster than ever on Arm CPUs.
By integrating KleidiAI with ExecuTorch and developing optimized quantization schemes, we have achieved speeds of over 350 tokens per second on the prefill stage for generative AI workloads on mobile.
Llama.cpp
To demonstrate the capability of Arm-based CPUs for LLM inferencing, Arm and our partners are optimizing the int4 and int8 kernels implemented in llama.cpp to leverage these newer instructions.
Phi 3 3.8B
Due to our optimizations, the time-to-first token (TTFT) for Microsoft’s Phi 3 LLM is accelerated by around 190% when running a chatbot demo on the Arm Cortex-X925 CPU, which is used in premium smartphones.
Llama 3 8B
Running a text generation demo on Graviton3 processors with our optimizations achieves a 2.5 times performance uplift for TTFT and over 35 tokens / second in the text generation phase, which is more than sufficient for real-time use cases.
MediaPipe
Arm’s partnership with Google AI Edge on MediaPipe and XNNPACK is accelerating AI workloads on current and future Arm CPUs. This enables developers to deliver outstanding AI performance for mobile, web, edge and IoT.
Gemma 1 2B
Arm collaborated with Google AI Edge to integrate KleidiAI with their MediaPipe framework, which supports numerous LLMs, such as Gemma and Falcon.
Thanks to KleidiAI integration via XNNPACK, we have seen a 30% acceleration in TTFT when running a chatbot demo on the Gemma 2B LLM on Arm-based premium smartphones.
Hunyuan
Tencent’s Hunyuan AI framework supports Hunyuan LLM, a universal model that enables AI capabilities across a wide range of devices, including smartphones.
Hunyuan
Arm has been working with Tencent to integrate Kleidi technologies into Hunyuan, its LLM with over 100B parameters.
The partnership was announced at the 2024 Tencent Global Digital Ecosystem Summit and can have a positive impact on real-world workloads.
Key Developer Technologies for Accelerating CPU Performance
Arm Kleidi includes the latest developer enablement technologies designed to advance AI model capability, accuracy, and speed.
KleidiAI and KleidiCV libraries are lightweight kernels designed to make it easy for machine learning (ML) and computer vision (CV) frameworks to target optimum performance and leverage the latest features for enhancing AI and CV in Arm CPU-based designs.
A fully comprehensive and flexible library that enables independent software vendors to source ML functions optimized for Cortex-A and Neoverse CPUs. The library is OS agnostic and is portable to Android, Linux, and bare metal systems.
Simplifying AI Deployment
Arm is committed to maximizing the ease and speed of AI deployment for developers. Kleidi is just one of the ways we are making AI optimizations accessible to millions.
Unleashing CPU Performance at Scale
Kleidi enables easy optimization across the full range of Arm Neoverse and Arm Cortex-A CPUs. These technologies leverage advanced features in the Arm architecture, such as Arm Scalable Vector Extensions (SVE), and Arm Scalable Matrix Extensions (SME), which target accelerated AI performance.
