SupraSNN introduces a superscalar-inspired SNN accelerator with decoupled synapse and neuron units, multi-cast/merge trees, and partitioning/scheduling that reports 47.6% lower latency and 5.6x better energy efficiency than prior FPGA SNN designs on MNIST and SHD tasks.
Securing hard drives with the Security Protocol and Data Model (SPDM)
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
A UEFI system with SPDM authenticates connected devices and restricts them to allowed ones, with emulation showing 13% more instructions and 8% more CPU cycles during boot.
citing papers explorer
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SupraSNN: Exploiting Synapse-Level Parallelism in Spiking Neural Network Accelerators through Co-Optimized Mapping and Scheduling
SupraSNN introduces a superscalar-inspired SNN accelerator with decoupled synapse and neuron units, multi-cast/merge trees, and partitioning/scheduling that reports 47.6% lower latency and 5.6x better energy efficiency than prior FPGA SNN designs on MNIST and SHD tasks.
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A UEFI System with SPDM to Protect Against Unauthorized Device Connections
A UEFI system with SPDM authenticates connected devices and restricts them to allowed ones, with emulation showing 13% more instructions and 8% more CPU cycles during boot.