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05/24/2023
READ: Recurrent Adaptation of Large Transformers
Fine-tuning large-scale Transformers has led to the explosion of many AI...
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05/02/2023
Design Space Exploration and Optimization for Carbon-Efficient Extended Reality Systems
As computing hardware becomes more specialized, designing environmentall...
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04/01/2023
GreenScale: Carbon-Aware Systems for Edge Computing
To improve the environmental implications of the growing demand of compu...
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03/10/2023
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference
Mixture-of-Experts (MoE) models have gained popularity in achieving stat...
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02/21/2023
MP-Rec: Hardware-Software Co-Design to Enable Multi-Path Recommendation
Deep learning recommendation systems serve personalized content under di...
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01/08/2023
FlexShard: Flexible Sharding for Industry-Scale Sequence Recommendation Models
Sequence-based deep learning recommendation models (DLRMs) are an emergi...
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11/30/2022
FedGPO: Heterogeneity-Aware Global Parameter Optimization for Efficient Federated Learning
Federated learning (FL) has emerged as a solution to deal with the risk ...
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11/09/2022
RecD: Deduplication for End-to-End Deep Learning Recommendation Model Training Infrastructure
We present RecD (Recommendation Deduplication), a suite of end-to-end in...
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08/25/2022
Understanding the Power of Evolutionary Computation for GPU Code Optimization
Achieving high performance for GPU codes requires developers to have sig...
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08/17/2022
Understanding Scaling Laws for Recommendation Models
Scale has been a major driving force in improving machine learning perfo...
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07/20/2022
DataPerf: Benchmarks for Data-Centric AI Development
Machine learning (ML) research has generally focused on models, while th...
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06/07/2022
FEL: High Capacity Learning for Recommendation and Ranking via Federated Ensemble Learning
Federated learning (FL) has emerged as an effective approach to address ...
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06/03/2022
Infinite Recommendation Networks: A Data-Centric Approach
We leverage the Neural Tangent Kernel and its equivalence to training in...
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05/30/2022
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity
Federated learning (FL) is an effective mechanism for data privacy in re...
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03/14/2022
Hercules: Heterogeneity-Aware Inference Serving for At-Scale Personalized Recommendation
Personalized recommendation is an important class of deep-learning appli...
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01/25/2022
RecShard: Statistical Feature-Based Memory Optimization for Industry-Scale Neural Recommendation
We propose RecShard, a fine-grained embedding table (EMB) partitioning a...
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01/25/2022
A Holistic Approach for Designing Carbon Aware Datacenters
Technology companies have been leading the way to a renewable energy tra...
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01/13/2022
On Sampling Collaborative Filtering Datasets
We study the practical consequences of dataset sampling strategies on th...
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11/08/2021
Papaya: Practical, Private, and Scalable Federated Learning
Cross-device Federated Learning (FL) is a distributed learning paradigm ...
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10/30/2021
Sustainable AI: Environmental Implications, Challenges and Opportunities
This paper explores the environmental impact of the super-linear growth ...
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08/20/2021
Understanding and Co-designing the Data Ingestion Pipeline for Industry-Scale RecSys Training
The data ingestion pipeline, responsible for storing and preprocessing t...
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08/15/2021
Socio-Technological Challenges and Opportunities: Paths Forward
Advancements in digital technologies have a bootstrapping effect. The pa...
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07/16/2021
AutoFL: Enabling Heterogeneity-Aware Energy Efficient Federated Learning
Federated learning enables a cluster of decentralized mobile devices at ...
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07/11/2021
SVP-CF: Selection via Proxy for Collaborative Filtering Data
We study the practical consequences of dataset sampling strategies on th...
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05/26/2021
Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale
Tremendous success of machine learning (ML) and the unabated growth in M...
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05/18/2021
RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance
Deep learning recommendation systems must provide high quality, personal...
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01/29/2021
RecSSD: Near Data Processing for Solid State Drive Based Recommendation Inference
Neural personalized recommendation models are used across a wide variety...
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01/25/2021
TT-Rec: Tensor Train Compression for Deep Learning Recommendation Models
The memory capacity of embedding tables in deep learning recommendation ...
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11/11/2020
Understanding Training Efficiency of Deep Learning Recommendation Models at Scale
The use of GPUs has proliferated for machine learning workflows and is n...
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11/05/2020
CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery
The paper proposes and optimizes a partial recovery training system, CPR...
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11/04/2020
Understanding Capacity-Driven Scale-Out Neural Recommendation Inference
Deep learning recommendation models have grown to the terabyte scale. Tr...
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10/28/2020
Chasing Carbon: The Elusive Environmental Footprint of Computing
Given recent algorithm, software, and hardware innovation, computing has...
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10/10/2020
Cross-Stack Workload Characterization of Deep Recommendation Systems
Deep learning based recommendation systems form the backbone of most per...
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05/06/2020
AutoScale: Optimizing Energy Efficiency of End-to-End Edge Inference under Stochastic Variance
Deep learning inference is increasingly run at the edge. As the programm...
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04/17/2020
GEVO: GPU Code Optimization using EvolutionaryComputation
GPUs are a key enabler of the revolution in machine learning and high pe...
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04/17/2020
GEVO: GPU Code Optimization using Evolutionary Computation
GPUs are a key enabler of the revolution in machine learning and high pe...
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01/08/2020
DeepRecSys: A System for Optimizing End-To-End At-scale Neural Recommendation Inference
Neural personalized recommendation is the corner-stone of a wide collect...
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12/30/2019
RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing
Personalized recommendation systems leverage deep learning models and ac...
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11/06/2019
MLPerf Inference Benchmark
Machine-learning (ML) hardware and software system demand is burgeoning....
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10/02/2019
MLPerf Training Benchmark
Machine learning is experiencing an explosion of software and hardware s...
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08/13/2019
Exploiting Parallelism Opportunities with Deep Learning Frameworks
State-of-the-art machine learning frameworks support a wide variety of d...
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06/06/2019
The Architectural Implications of Facebook's DNN-based Personalized Recommendation
The widespread application of deep learning has changed the landscape of...
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05/31/2019
