1 citations · 1 across the 7 of their papers we have counts for
7 papers
CryoZip: An Efficient Cryogenic Compressor for Quantum Error Correction Syndromes
Guanchen Tao, Alexander Knapen, Jacob Mack +4
Scaling fault tolerant quantum computing is increasingly constrained by the limited bandwidth and power budget across the 4 K to room temperature (RT) interface. We present CryoZip…
Mitigating Classical Resource Costs in Quantum Error Correction via Generalized qLDPC Predecoding
Alexander Knapen, Junyi Luo, Guanchen Tao +6
Large-scale fault-tolerant quantum computing (FTQC) will require quantum-classical interfaces (QCIs) that orchestrate real-time decoding over thousands to millions of logical qubit…
Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs
Pierre Abillama, Changwoo Lee, Juechu Dong +3
Recent advances in transformer-based foundation models have made them the default choice for many tasks, but their rapidly growing size makes fitting a full model on a single GPU i…
Pinball: A Cryogenic Predecoder for Surface Code Decoding Under Circuit-Level Noise
Alexander Knapen, Guanchen Tao, Jacob Mack +5
Scaling fault tolerant quantum computers, especially cryogenic systems based on the surface code, to millions of qubits is challenging due to poorly-scaling data processing and pow…
Microscopic Robots That Sense, Think, Act, and Compute
Maya M. Lassiter, Jungho Lee, Kyle Skelil +7
While miniaturization has been a goal in robotics for nearly 40 years, roboticists have struggled to access sub-millimeter dimensions without making sacrifices to on-board informat…
SQ-DM: Accelerating Diffusion Models with Aggressive Quantization and Temporal Sparsity
Zichen Fan, Steve Dai, Rangharajan Venkatesan +2
Diffusion models have gained significant popularity in image generation tasks. However, generating high-quality content remains notably slow because it requires running model infer…
ConSmax: Hardware-Friendly Alternative Softmax with Learnable Parameters
Shiwei Liu, Guanchen Tao, Yifei Zou +7
The self-attention mechanism distinguishes transformer-based large language models (LLMs) apart from convolutional and recurrent neural networks. Despite the performance improvemen…