research
∙
02/27/2023
Full Stack Optimization of Transformer Inference: a Survey
Recent advances in state-of-the-art DNN architecture design have been mo...
share
research
∙
05/05/2021
CoSA: Scheduling by Constrained Optimization for Spatial Accelerators
Recent advances in Deep Neural Networks (DNNs) have led to active develo...
research
∙
04/26/2021
HAO: Hardware-aware neural Architecture Optimization for Efficient Inference
Automatic algorithm-hardware co-design for DNN has shown great success i...
research
∙
11/20/2020
HAWQV3: Dyadic Neural Network Quantization
Quantization is one of the key techniques used to make Neural Networks (...
research
∙
06/12/2020
CoDeNet: Algorithm-hardware Co-design for Deformable Convolution
Deploying deep learning models on embedded systems for computer vision t...
research
∙
05/27/2020
ProTuner: Tuning Programs with Monte Carlo Tree Search
We explore applying the Monte Carlo Tree Search (MCTS) algorithm in a no...
research
∙
03/02/2020
AutoPhase: Juggling HLS Phase Orderings in Random Forests with Deep Reinforcement Learning
The performance of the code a compiler generates depends on the order in...
research
∙
02/19/2020
Algorithm-hardware Co-design for Deformable Convolution
FPGAs provide a flexible and efficient platform to accelerate rapidly-ch...
research
∙
03/05/2019
Integrating NVIDIA Deep Learning Accelerator (NVDLA) with RISC-V SoC on FireSim
NVDLA is an open-source deep neural network (DNN) accelerator which has ...
research
∙
01/15/2019
AutoPhase: Compiler Phase-Ordering for High Level Synthesis with Deep Reinforcement Learning
The performance of the code generated by a compiler depends on the order...
research
∙
11/21/2018