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cs.LG updates on arXiv.org

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Reconfigurable Computing Challenge: Transformer for Jet T...
[Submitted on 16 Jun 2026] · 2026-06-17 · via cs.LG updates on arXiv.org

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Abstract:Transformer-based models achieve strong performance for jet tagging at the CERN LHC, but deploying them in low-latency, resource-constrained trigger systems is challenging. We present an initial implementation of a quantized, integer-only transformer for jet tagging on the AMD Versal AI Engine (AIE), mapping dense and multi-head attention (MHA) layers to AIE tiles. The main contribution is a reusable software framework that represents transformer layers as composable AIE building blocks and automatically generates the corresponding Vitis graph code from a high-level Python model description. This framework provides a foundation for future research and is released as open-source software at this https URL.

Submission history

From: Gram Koski [view email]
[v1] Tue, 16 Jun 2026 04:22:06 UTC (556 KB)