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02/12/2021
Neural Architecture Search as Program Transformation Exploration
Improving the performance of deep neural networks (DNNs) is important to...
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11/21/2020
Deep Data Flow Analysis
Compiler architects increasingly look to machine learning when building ...
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08/27/2020
M3: Semantic API Migrations
Library migration is a challenging problem, where most existing approach...
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06/17/2020
Optimizing Grouped Convolutions on Edge Devices
When deploying a deep neural network on constrained hardware, it is poss...
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06/10/2020
Retrofitting Symbolic Holes to LLVM IR
Symbolic holes are one of the fundamental building blocks of solver-aide...
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02/20/2020
Performance Aware Convolutional Neural Network Channel Pruning for Embedded GPUs
Convolutional Neural Networks (CNN) are becoming a common presence in ma...
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07/12/2019
Augmenting Type Signatures for Program Synthesis
Effective program synthesis requires a way to minimise the number of can...
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06/10/2019
BlockSwap: Fisher-guided Block Substitution for Network Compression
The desire to run neural networks on low-capacity edge devices has led t...
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10/24/2018
HAKD: Hardware Aware Knowledge Distillation
Despite recent developments, deploying deep neural networks on resource ...
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10/24/2018
Distilling with Performance Enhanced Students
The task of accelerating large neural networks on general purpose hardwa...
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10/10/2018
Pruning neural networks: is it time to nip it in the bud?
Pruning is a popular technique for compressing a neural network: a large...
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09/19/2018
Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks
Convolutional Neural Networks (CNNs) are extremely computationally deman...
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08/21/2018
SLAMBench2: Multi-Objective Head-to-Head Benchmarking for Visual SLAM
SLAM is becoming a key component of robotics and augmented reality (AR) ...
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05/09/2018
