The demand for AI is expanding beyond traditional GPU-based data centers to diverse environments, including edge and hybrid clouds. VMware and Intel have joined forces to bring AI capabilities to CPU-driven infrastructure, demonstrating how AI workloads can thrive without GPUs by leveraging Intel's 4th Gen Xeon Scalable Processors and VMware's Private AI infrastructure.
VMware Private AI integrates AI infrastructure with privacy, compliance, and security, built on VMware Cloud Foundation (VCF). Paired with Intel’s Advanced Matrix Extensions (AMX), it enables scalable and efficient AI operations without requiring specialized hardware like GPUs.
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Intel 4th Gen Xeon Scalable Processors with AMX:
AMX accelerates both AI training and inference directly within the CPU, optimizing performance for workloads like large language models (LLMs). -
VMware Cloud Foundation:
This software-defined platform virtualizes compute, storage, and networking, providing a unified management interface for containerized AI workloads using VMware Tanzu Kubernetes Grid (TKG).
In a real-world application, VMware and Intel tested the Llama 2-7B model on Intel's hardware, showing how AMX-enabled processors efficiently handle inference workloads. Key results include:
- Inference latency under 50ms for small batches with INT8 precision.
- Scalability for multiple instances per socket with sub-100ms latency, even at high token counts.
- Intel's AMX technology speeds up inference by up to 1.8x compared to BF16 models.
- VMware's integration with Kubernetes makes deploying AI models on existing infrastructure fast and seamless.
This solution is ideal for businesses looking to expand AI capabilities without investing heavily in GPU infrastructure. It offers:
- Cost Efficiency: Leverage existing CPU resources for AI tasks.
- Flexibility: Run AI workloads across cloud, edge, and on-premise environments.
- Scalability: Easily manage resource-intensive tasks like LLM inference with VMware's orchestration tools.
By combining VMware and Intel technologies, enterprises can unlock the full potential of AI with optimized infrastructure, reducing costs and simplifying deployment.
