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05/17/2023
ACRoBat: Optimizing Auto-batching of Dynamic Deep Learning at Compile Time
Dynamic control flow is an important technique often used to design expr...
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02/08/2023
ED-Batch: Efficient Automatic Batching of Dynamic Neural Networks via Learned Finite State Machines
Batching has a fundamental influence on the efficiency of deep neural ne...
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11/18/2022
PIM-tree: A Skew-resistant Index for Processing-in-Memory
The performance of today's in-memory indexes is bottlenecked by the memo...
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06/01/2022
Federated Learning under Distributed Concept Drift
Federated Learning (FL) under distributed concept drift is a largely une...
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05/28/2022
Spatial Locality and Granularity Change in Caching
Caches exploit temporal and spatial locality to allow a small memory to ...
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10/19/2021
The CoRa Tensor Compiler: Compilation for Ragged Tensors with Minimal Padding
There is often variation in the shape and size of input data used for de...
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05/17/2021
MetaSys: A Practical Open-Source Metadata Management System to Implement and Evaluate Cross-Layer Optimizations
This paper introduces the first open-source FPGA-based infrastructure, M...
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03/13/2020
DriftSurf: A Risk-competitive Learning Algorithm under Concept Drift
When learning from streaming data, a change in the data distribution, al...
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12/10/2019
Advances and Open Problems in Federated Learning
Federated learning (FL) is a machine learning setting where many clients...
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10/27/2019
Semi-Asymmetric Parallel Graph Algorithms for NVRAMs
Emerging non-volatile main memory (NVRAM) technologies provide novel fea...
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10/01/2019
The Non-IID Data Quagmire of Decentralized Machine Learning
Many large-scale machine learning (ML) applications need to train ML mod...
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03/29/2019
SysML: The New Frontier of Machine Learning Systems
Machine learning (ML) techniques are enjoying rapidly increasing adoptio...
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05/15/2018
The Parallel Persistent Memory Model
We consider a parallel computational model that consists of P processors...
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05/07/2018
RowClone: Accelerating Data Movement and Initialization Using DRAM
In existing systems, to perform any bulk data movement operation (copy o...
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05/02/2018
Decoupling GPU Programming Models from Resource Management for Enhanced Programming Ease, Portability, and Performance
The application resource specification--a static specification of severa...
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03/20/2018
MLtuner: System Support for Automatic Machine Learning Tuning
MLtuner automatically tunes settings for training tunables (such as the ...
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02/07/2018
Zorua: Enhancing Programming Ease, Portability, and Performance in GPUs by Decoupling Programming Models from Resource Management
The application resource specification--a static specification of severa...
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01/10/2018
Focus: Querying Large Video Datasets with Low Latency and Low Cost
Large volumes of videos are continuously recorded from cameras deployed ...
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11/30/2016