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: As DNNs are developing rapidly, the computational and memory burden imposed on hardware systems grows exponentially. This becomes even more severe for large language models (LLMs) and ...

Abstract: In this paper, we investigate a joint task offloading, deep neural network (DNN) model pruning, and edge computing resource allocation (JOPA) problem for supporting a fault detection service ...