Tag: inference workloads
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Hacker News: Nvidia CEO says his AI chips are improving faster than Moore’s Law
Source URL: https://techcrunch.com/2025/01/07/nvidia-ceo-says-his-ai-chips-are-improving-faster-than-moores-law/ Source: Hacker News Title: Nvidia CEO says his AI chips are improving faster than Moore’s Law Feedly Summary: Comments AI Summary and Description: Yes Summary: Jensen Huang, CEO of Nvidia, asserts that the performance of the company’s AI chips is advancing at a pace exceeding the historical benchmark of Moore’s Law. This…
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Cloud Blog: Announcing the general availability of Trillium, our sixth-generation TPU
Source URL: https://cloud.google.com/blog/products/compute/trillium-tpu-is-ga/ Source: Cloud Blog Title: Announcing the general availability of Trillium, our sixth-generation TPU Feedly Summary: The rise of large-scale AI models capable of processing diverse modalities like text and images presents a unique infrastructural challenge. These models require immense computational power and specialized hardware to efficiently handle training, fine-tuning, and inference. Over…
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AWS News Blog: New Amazon EC2 P5en instances with NVIDIA H200 Tensor Core GPUs and EFAv3 networking
Source URL: https://aws.amazon.com/blogs/aws/new-amazon-ec2-p5en-instances-with-nvidia-h200-tensor-core-gpus-and-efav3-networking/ Source: AWS News Blog Title: New Amazon EC2 P5en instances with NVIDIA H200 Tensor Core GPUs and EFAv3 networking Feedly Summary: Amazon EC2 P5en instances deliver up to 3,200 Gbps network bandwidth with EFAv3 for accelerating deep learning, generative AI, and HPC workloads with unmatched efficiency. AI Summary and Description: Yes **Summary:**…
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Cloud Blog: Data loading best practices for AI/ML inference on GKE
Source URL: https://cloud.google.com/blog/products/containers-kubernetes/improve-data-loading-times-for-ml-inference-apps-on-gke/ Source: Cloud Blog Title: Data loading best practices for AI/ML inference on GKE Feedly Summary: As AI models increase in sophistication, there’s increasingly large model data needed to serve them. Loading the models and weights along with necessary frameworks to serve them for inference can add seconds or even minutes of scaling…
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Cloud Blog: Powerful infrastructure innovations for your AI-first future
Source URL: https://cloud.google.com/blog/products/compute/trillium-sixth-generation-tpu-is-in-preview/ Source: Cloud Blog Title: Powerful infrastructure innovations for your AI-first future Feedly Summary: The rise of generative AI has ushered in an era of unprecedented innovation, demanding increasingly complex and more powerful AI models. These advanced models necessitate high-performance infrastructure capable of efficiently scaling AI training, tuning, and inferencing workloads while optimizing…
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Cloud Blog: Save on GPUs: Smarter autoscaling for your GKE inferencing workloads
Source URL: https://cloud.google.com/blog/products/containers-kubernetes/tuning-the-gke-hpa-to-run-inference-on-gpus/ Source: Cloud Blog Title: Save on GPUs: Smarter autoscaling for your GKE inferencing workloads Feedly Summary: While LLM models deliver immense value for an increasing number of use cases, running LLM inference workloads can be costly. If you’re taking advantage of the latest open models and infrastructure, autoscaling can help you optimize…
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Cloud Blog: We tested Intel’s AMX CPU accelerator for AI. Here’s what we learned
Source URL: https://cloud.google.com/blog/products/identity-security/we-tested-intels-amx-cpu-accelerator-for-ai-heres-what-we-learned/ Source: Cloud Blog Title: We tested Intel’s AMX CPU accelerator for AI. Here’s what we learned Feedly Summary: At Google Cloud, we believe that cloud computing will increasingly shift to private, encrypted services where users can be confident that their software and data are not being exposed to unauthorized actors. In support…
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The Register: Supermicro crams 18 GPUs into a 3U AI server that’s a little slow by design
Source URL: https://www.theregister.com/2024/10/09/supermicro_sys_322gb_nr_18_gpu_server/ Source: The Register Title: Supermicro crams 18 GPUs into a 3U AI server that’s a little slow by design Feedly Summary: Can handle edge inferencing or run a 64 display command center GPU-enhanced servers can typically pack up to eight of the accelerators, but Supermicro has built a box that manages to…