To effectively utilize heterogeneous specialized hardware units in modern GPUs, such as TensorCores and Tensor Memory Accelerators, this paper introduces PipeThreader, a new DNN compiler. PipeThreader ...
To speed up computation, deep neural networks (DNNs) usually rely on highly optimized tensor operators. Despite the effectiveness, tensor operators are often defined empirically with ad hoc semantics.
The package utilizes the MQTT protocol to communicate with your AIRMX devices. Once connected to the server, it constantly monitors the status updates from your machines. Additionally, it provides a ...
Abstract: This paper presents a Posit-based Mixed Precision (PMP) framework for deep neural network (DNN) training and inference, leveraging Posit32, Posit16, and Posit8 across different computational ...
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AI Mode will preface its list of sources with an AI-generated snippet about why they’re relevant. AI Mode will preface its list of sources with an AI-generated snippet about why they’re relevant. is a ...
Abstract: Recently, various pipeline parallelism strategies are proposed to tackle the scalability problem of training a large DNN model on a distributed system. However, most of the works focus on ...