In modern software development, time is an incredibly valuable resource, especially during the compilation process. For developers working with CUDA C++ on large-scale GPU-accelerated applications, optimizing compile times can significantly enhance productivity and streamline the entire development cycle. When using the compiler for offline compilation, efficient compilation times enable��
]]>In the wake of ever-growing power demands, power systems optimization (PSO) of power grids is crucial for ensuring efficient resource management, sustainability, and energy security. The Eastern Interconnection, a major North American power grid, consists of approximately 70K nodes (Figure 1). Aside from sheer size, optimizing such a grid is complicated by uncertainties such as catastrophic��
]]>In the high-frequency trading world, thousands of market participants interact daily. In fact, high-frequency trading accounts for more than half of the US equity trading volume, according to the paper High-Frequency Trading Synchronizes Prices in Financial Markets. Market makers are the big players on the sell side who provide liquidity in the market. Speculators are on the buy side��
]]>The most exciting computing applications currently rely on training and running inference on complex AI models, often in demanding, real-time deployment scenarios. High-performance, accelerated AI platforms are needed to meet the demands of these applications and deliver the best user experiences. New AI models are constantly being invented to enable new capabilities��
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