Machine learning-based weather prediction has emerged as a promising complement to traditional numerical weather prediction (NWP) models. Models such as NVIDIA FourCastNet have demonstrated that the computational time for generating weather forecasts can be reduced from hours to mere seconds, a significant improvement to current NWP-based workflows. Traditional methods are formulated from…
]]>Decades of computer science history have been devoted to devising solutions for efficient storage and retrieval of information. Hash maps (or hash tables) are a popular data structure for information storage given their amortized, constant-time guarantees for the insertion and retrieval of elements. However, despite their prevalence, hash maps are seldom discussed in the context of GPU…
]]>Efficient pipeline design is crucial for data scientists. When composing complex end-to-end workflows, you may choose from a wide variety of building blocks, each of them specialized for a dedicated task. Unfortunately, repeatedly converting between data formats is an error-prone and performance-degrading endeavor. Let’s change that! In this blog series, we discuss different aspects of…
]]>Efficient pipeline design is crucial for data scientists. When composing complex end-to-end workflows, you may choose from a wide variety of building blocks, each of them specialized for a dedicated task. Unfortunately, repeatedly converting between data formats is an error-prone and performance-degrading endeavor. Let’s change that! In this post series, we discuss different aspects of…
]]>Efficient pipeline design is crucial for data scientists. When composing complex end-to-end workflows, you may choose from a wide variety of building blocks, each of them specialized for a dedicated task. Unfortunately, repeatedly converting between data formats is an error-prone and performance-degrading endeavor. Let’s change that! In this post series, we discuss different aspects of…
]]>To say it with the words of Eamonn Keogh: “Time series is a ubiquitous and increasingly prevalent type of data […]”. Virtually any incrementally measured signal, be it along a time axis or a linearly ordered set, can be treated as time series. Examples include electrocardiograms, temperature or voltage measurements, audio, server logs, but also heavy-weight data such as video and time-resolved MRI…
]]>Imagine that you have just finished implementing an awesome, interactive, deep learning pipeline on your NVIDIA-accelerated data science workstation using OpenCV for capturing your webcam stream and rendering the output. A colleague of yours mentions that exploiting the novel TF32 compute mode of the Ampere microarchitecture third-generation Tensor Cores might significantly accelerate your…
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