Future Vertical Lift: Senior Leaders Restructured the Army Aviation Portfolio to Reduce Costs
What GAO Found The Army relies on what it calls vertical lift systems, primarily helicopters, to accomplish reconnaissance and attack missions and move troops and equipment to and around the battlefield. In its 2019 modernization strategy, the Army identified developing its Future Vertical Lift portfolio as a priority. This portfolio included two crewed and one uncrewed aircraft. Future Attack Reconnaissance Aircraft (FARA)—intended to provide reconnaissance, attack, and aerial security capabilities, and estimated to cost $5.3 billion for development and procurement. Future Long Range Assault Aircraft (FLRAA)—a medium-sized assault and utility aircraft that would deliver speed, range, agility, endurance, and sustainability improvements compared to current Black Hawk helicopters. Future Tac
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launchannounceproductDeep Dive into vLLM: How PagedAttention & Continuous Batching Revolutionized LLM Inference
<p>Serving Large Language Models (LLMs) in production is notoriously difficult and expensive. While researchers focus heavily on making models smarter or training them faster, the operational bottleneck for deploying these models at scale almost always comes down to <strong>inference throughput</strong> and <strong>memory management</strong>.</p> <p>Enter <strong>vLLM</strong>, an open-source library that took the AI infrastructure world by storm. By tackling the root causes of GPU memory waste, vLLM achieves 2x to 4x higher throughput compared to naive HuggingFace Transformers implementations.</p> <p>Let's dive deep into the architectural breakthroughs that make vLLM the gold standard for high-throughput LLM serving: <strong>PagedAttention</strong> and <strong>Continuous Batching</strong>
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