Silhouette: Toward Performance-Conscious and Transferable CPU Embeddings

Abdul Wasay; Tarikul Islam Papon

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Silhouette: Toward Performance-Conscious and Transferable CPU Embeddings

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arxiv 2212.08046 v1 pith:76NP53EE submitted 2022-12-15 cs.LG

Silhouette: Toward Performance-Conscious and Transferable CPU Embeddings

Tarikul Islam Papon , Abdul Wasay This is my paper

classification cs.LG

keywords dataembeddingssetsdifferentenablelearningsilhouettetransfer

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Learned embeddings are widely used to obtain concise data representation and enable transfer learning between different data sets and tasks. In this paper, we present Silhouette, our approach that leverages publicly-available performance data sets to learn CPU embeddings. We show how these embeddings enable transfer learning between data sets of different types and sizes. Each of these scenarios leads to an improvement in accuracy for the target data set.

Silhouette: Toward Performance-Conscious and Transferable CPU Embeddings

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