AI Computing Platform Laboratory
Department of Computer Science and Engineering, Artificial Intelligence Convergence, Ewha Womans University
The AI Computing Platform Laboratory (ACPL) has been a lab of excellence for efficient AI hardware & software research since its founding in 2021.
Our main research goal is to accelerate AI model in a faster and energy-efficient way through HW/SW co-design. Specifically, our research interests include:
- Designing Neural Processing Unit (NPU) and domain-specific hardware
- Making AI model efficient, such as quantization, pruning, and knowledge distillation
- Hardware-aware neural architecture search (HW-Aware NAS) and neural architecture accelerator search (NAAS)
- Processing-in-memory (PIM)
news
| Jul 01, 2024 | Jiyeon Ha and Minseo Kim have joined our group as an undergraduate research intern. Welcome! |
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| Jun 22, 2024 | Professor Sim will be leaving to San Fransisco, USA to attend DAC 2024. Accordingly, he will be out of office from June 22nd to June 30th. |
| May 29, 2024 | Our lab has three papers accepted for presentation at 21st International SoC Design Conference (ISOCC). |
| Apr 30, 2024 | Our lab has one paper accepted for publication in IEEE Access. |
| Apr 22, 2024 | Sunmin Lee has joined our group as an undergraduate research intern. Welcome! |
latest publications
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AcceptedAn Energy-Efficient Hardware Accelerator for On-Device Inference of YOLOXIn 2024 21st International SoC Design Conference (ISOCC)
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AcceptedBS2: Bit-Serial Architecture Exploiting Weight Bit Sparsity for Efficient Deep Learning AccelerationIn 2024 21st International SoC Design Conference (ISOCC)
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AcceptedAlphaAccelerator: An Automatic Neural FPGA Accelerator Design Framework Based on GNNsIn 2024 21st International SoC Design Conference (ISOCC)
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SCIEQ-LAtte: An Efficient and Versatile LSTM Model for Quantized Attention-Based Time Series Forecasting in Building Energy ApplicationsIEEE Access, vol.12, pp.69325-69341, 2024