🏛️ The Hardware Architecture Crypt
cs.AR: Where Hardware Architecture papers rest without their code.
732
Total Papers
583
No Code
10
Twilight
139
Has Code
19.0%
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A survey on FPGA-based accelerator for ML models
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Computation vs. Communication Scaling for Future Transformers on Future Hardware
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PhotoFourier: A Photonic Joint Transform Correlator-Based Neural Network Accelerator
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MegIS: High-Performance, Energy-Efficient, and Low-Cost Metagenomic Analysis with In-Storage Processing
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SCAR: Scheduling Multi-Model AI Workloads on Heterogeneous Multi-Chiplet Module Accelerators
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Anda: Unlocking Efficient LLM Inference with a Variable-Length Grouped Activation Data Format
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A Heterogeneous Chiplet Architecture for Accelerating End-to-End Transformer Models
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Evaluating Emerging AI/ML Accelerators: IPU, RDU, and NVIDIA/AMD GPUs
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Systolic-CNN: An OpenCL-defined Scalable Run-time-flexible FPGA Accelerator Architecture for Accelerating Convolutional Neural Network Inference in Cloud/Edge Computing
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STOMP: A Tool for Evaluation of Scheduling Policies in Heterogeneous Multi-Processors
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Special Session: Towards an Agile Design Methodology for Efficient, Reliable, and Secure ML Systems
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FlexNN: A Dataflow-aware Flexible Deep Learning Accelerator for Energy-Efficient Edge Devices
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Memory-Centric Computing: Recent Advances in Processing-in-DRAM
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Automatically Improving LLM-based Verilog Generation using EDA Tool Feedback
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ExPAN(N)D: Exploring Posits for Efficient Artificial Neural Network Design in FPGA-based Systems
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Thales: Formulating and Estimating Architectural Vulnerability Factors for DNN Accelerators
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VEDLIoT: Very Efficient Deep Learning in IoT
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Memory-Centric Computing
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Bit-balance: Model-Hardware Co-design for Accelerating NNs by Exploiting Bit-level Sparsity
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Scalable and Efficient Virtual Memory Sharing in Heterogeneous SoCs with TLB Prefetching and MMU-Aware DMA Engine
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Near-Data Processing for Differentiable Machine Learning Models
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DSL-based Design Space Exploration for Temporal and Spatial Parallelism of Custom Stream Computing
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