Accelerating Machine Learning with Open Source Warp-CTC

Today Baidu’s Silicon Valley AI Lab (SVAIL) released Warp-CTC open source software for the machine learning community. Warp-CTC is an implementation of the #‎CTC algorithm for #‎CPUs and NVIDIA #‎GPUs. With Warp-CTC, researchers can directly call the C library from a project or implement Warp-CTC with #‎Torch using supplied bindings. According to SVAIL, Warp-CTC is 10-400x faster than current implementations. It makes end-to-end deep learning easier and faster so researchers can make progress more rapidly. Connectionist Temporal Classification (CTC) is a loss function useful for performing supervised learning on sequence data, without needing an alignment between input data and labels. For example, CTC can be used to train end-to-end systems for speech recognition, which is how they we have been using it at Baidu’s Silicon Valley AI Lab. SVAIL engineers developed Warp-CTC…


Link to Full Article: Accelerating Machine Learning with Open Source Warp-CTC

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