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Alluxio, a leading data platform provider for AI and analytics, has partnered with vLLM Production Stack, an open-source serving system developed by LMCache Lab at the University of Chicago, to significantly accelerate large language model (LLM) inference. This collaboration integrates advanced KV Cache management, dramatically enhancing AI infrastructure by providing faster response times, improved scalability, and cost-effective deployment options for enterprise applications.
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Alluxio, supplier of open source data store virtualization software using a virtual distributed file system with multi-tier caching, announced a strategic collaboration with the vLLM Production Stack, an open source implementation of a cluster-wide full-stack vLLM serving system developed by LMCache Lab at the University of Chicago.
Large language models (LLMs) are transforming industries with their ability to process vast amounts of data quickly. However, deploying these models efficiently remains a challenge. Slow inference speeds, high memory consumption, and complex scaling issues hinder seamless integration. To solve these problems, Alluxio and the vLLM Production Stack have joined forces. This partnership enhances LLM inference by improving performance, optimizing memory, and enabling scalability.
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Alluxio, a leading data platform provider for AI and analytics, has partnered with vLLM Production Stack, an open-source serving system developed by LMCache Lab at the University of Chicago, to significantly accelerate large language model (LLM) inference. This collaboration integrates advanced KV Cache management, dramatically enhancing AI infrastructure by providing faster response times, improved scalability, and cost-effective deployment options for enterprise applications.
Alluxio, supplier of open source data store virtualization software using a virtual distributed file system with multi-tier caching, announced a strategic collaboration with the vLLM Production Stack, an open source implementation of a cluster-wide full-stack vLLM serving system developed by LMCache Lab at the University of Chicago.
Large language models (LLMs) are transforming industries with their ability to process vast amounts of data quickly. However, deploying these models efficiently remains a challenge. Slow inference speeds, high memory consumption, and complex scaling issues hinder seamless integration. To solve these problems, Alluxio and the vLLM Production Stack have joined forces. This partnership enhances LLM inference by improving performance, optimizing memory, and enabling scalability.
Alluxio, a data platform for AI and analytics, announced a strategic collaboration with the vLLM Production Stack, an open-source LLM-serving system developed by LMCache Lab at the University of Chicago. The partnership aims to improve large language model (LLM) inference by optimizing KV Cache management, enhancing performance, scalability, and cost-efficiency.
Alluxio, the developer of the leading data platform for AI and analytics, today announced a strategic collaboration with the vLLM Production Stack, an open-source implementation of a cluster-wide full-stack vLLM serving system developed by LMCache Lab at the University of Chicago. This partnership aims to advance the next-generation AI infrastructure for large language model (LLM) inference.
This Saturday, March 8th, is International Women’s Day (IWD), a global celebration of the social, economic, cultural, and political achievement of women, as well as a call to action for accelerating gender equality. IWD seeks to make a positive difference for women by promoting strategies, resources, and activities that promote women’s advancements in overcoming significant barriers to gender equality that continue to exist well over a hundred years since its founding in 1911.
Saturday, March 8, is the global celebration of International Women’s Day (IWD), and a reminder that many issues still impact women’s equality and progress.
Tomorrow is International Women's Day 2025, a global day to celebrate the historic achievements of women in culture, technology, and society at large. And as such, it's important to take a moment to reflect on the progress that has been made in the fight for gender equality, as well as the challenges that still lie ahead.