research
∙
08/06/2023
Leveraging Cloud Computing to Make Autonomous Vehicles Safer
The safety of autonomous vehicles (AVs) depends on their ability to perf...
share
research
∙
03/13/2023
FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU
The high computational and memory requirements of large language model (...
research
∙
02/11/2023
Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks
Recent advances in instruction-following large language models (LLMs) ha...
research
∙
01/10/2023
Exoshuffle-CloudSort
We present Exoshuffle-CloudSort, a sorting application running on top of...
research
∙
11/09/2022
ZK-IMG: Attested Images via Zero-Knowledge Proofs to Fight Disinformation
Over the past few years, AI methods of generating images have been incre...
research
∙
10/19/2022
CLUTR: Curriculum Learning via Unsupervised Task Representation Learning
Reinforcement Learning (RL) algorithms are often known for sample ineffi...
research
∙
10/17/2022
Scaling up Trustless DNN Inference with Zero-Knowledge Proofs
As ML models have increased in capabilities and accuracy, so has the com...
research
∙
10/13/2022
Skyplane: Optimizing Transfer Cost and Throughput Using Cloud-Aware Overlays
Cloud applications are increasingly distributing data across multiple re...
research
∙
08/16/2022
Context-Aware Streaming Perception in Dynamic Environments
Efficient vision works maximize accuracy under a latency budget. These w...
research
∙
07/15/2022
POET: Training Neural Networks on Tiny Devices with Integrated Rematerialization and Paging
Fine-tuning models on edge devices like mobile phones would enable priva...
research
∙
06/28/2022
NumS: Scalable Array Programming for the Cloud
Scientists increasingly rely on Python tools to perform scalable distrib...
research
∙
05/19/2022
FogROS 2: An Adaptive and Extensible Platform for Cloud and Fog Robotics Using ROS 2
Mobility, power, and price points often dictate that robots do not have ...
research
∙
05/14/2022
The Sky Above The Clouds
Technology ecosystems often undergo significant transformations as they ...
research
∙
03/09/2022
Exoshuffle: Large-Scale Shuffle at the Application Level
Shuffle is a key primitive in large-scale data processing applications. ...
research
∙
01/21/2022
Representing Long-Range Context for Graph Neural Networks with Global Attention
Graph neural networks are powerful architectures for structured datasets...
research
∙
01/05/2022
Balsa: Learning a Query Optimizer Without Expert Demonstrations
Query optimizers are a performance-critical component in every database ...
research
∙
12/07/2021
MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance
Safe exploration is critical for using reinforcement learning (RL) in ri...
research
∙
11/05/2021
Grounded Graph Decoding Improves Compositional Generalization in Question Answering
Question answering models struggle to generalize to novel compositions o...
research
∙
07/22/2021
Accelerating Quadratic Optimization with Reinforcement Learning
First-order methods for quadratic optimization such as OSQP are widely u...
research
∙
06/18/2021
Scenic4RL: Programmatic Modeling and Generation of Reinforcement Learning Environments
The capability of reinforcement learning (RL) agent directly depends on ...
research
∙
06/11/2021
Online Learning of Competitive Equilibria in Exchange Economies
The sharing of scarce resources among multiple rational agents is one of...
research
∙
06/06/2021
PAC Best Arm Identification Under a Deadline
We study (ϵ, δ)-PAC best arm identification, where a decision-maker must...
research
∙
04/29/2021
ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training
The increasing size of neural network models has been critical for impro...
research
∙
04/16/2021
Pylot: A Modular Platform for Exploring Latency-Accuracy Tradeoffs in Autonomous Vehicles
We present Pylot, a platform for autonomous vehicle (AV) research and de...
research
∙
04/08/2021
Read-Write Quorum Systems Made Practical
Quorum systems are a powerful mechanism for ensuring the consistency of ...
research
∙
12/31/2020
Scaling Replicated State Machines with Compartmentalization [Technical Report]
State machine replication protocols, like MultiPaxos and Raft, are a cri...
research
∙
12/19/2020
Ekya: Continuous Learning of Video Analytics Models on Edge Compute Servers
Video analytics applications use edge compute servers for the analytics ...
research
∙
12/15/2020
Online Learning Demands in Max-min Fairness
We describe mechanisms for the allocation of a scarce resource among mul...
research
∙
11/25/2020
Distributed Reinforcement Learning is a Dataflow Problem
Researchers and practitioners in the field of reinforcement learning (RL...
research
∙
10/31/2020
Resource Allocation in Multi-armed Bandit Exploration: Overcoming Nonlinear Scaling with Adaptive Parallelism
We study exploration in stochastic multi-armed bandits when we have acce...
research
∙
10/12/2020
RackSched: A Microsecond-Scale Scheduler for Rack-Scale Computers (Technical Report)
Low-latency online services have strict Service Level Objectives (SLOs) ...
research
∙
07/18/2020
Matchmaker Paxos: A Reconfigurable Consensus Protocol [Technical Report]
State machine replication protocols, like MultiPaxos and Raft, are at th...
research
∙
07/15/2020
FetchSGD: Communication-Efficient Federated Learning with Sketching
Existing approaches to federated learning suffer from a communication bo...
research
∙
07/10/2020
Variable Skipping for Autoregressive Range Density Estimation
Deep autoregressive models compute point likelihood estimates of individ...
research
∙
07/09/2020
Contrastive Code Representation Learning
Machine-aided programming tools such as automated type predictors and au...
research
∙
06/15/2020
NeuroCard: One Cardinality Estimator for All Tables
Query optimizers rely on accurate cardinality estimates to produce good ...
research
∙
06/11/2020
Ansor : Generating High-Performance Tensor Programs for Deep Learning
High-performance tensor programs are crucial to guarantee efficient exec...
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
∙
04/19/2020
Mechanism Design with Bandit Feedback
We study a multi-round welfare-maximising mechanism design problem, wher...
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
∙
02/29/2020
Bipartisan Paxos: A Modular State Machine Replication Protocol
There is no shortage of state machine replication protocols. From Genera...
research
∙
02/13/2020
Hoplite: Efficient Collective Communication for Task-Based Distributed Systems
Collective communication systems such as MPI offer high performance grou...
research
∙
01/08/2020
HyperSched: Dynamic Resource Reallocation for Model Development on a Deadline
Prior research in resource scheduling for machine learning training work...
research
∙
12/29/2019
Hierarchical Variational Imitation Learning of Control Programs
Autonomous agents can learn by imitating teacher demonstrations of the i...
research
∙
11/30/2019
IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks
The practical usage of reinforcement learning agents is often bottleneck...
research
∙
11/22/2019
Gemmini: An Agile Systolic Array Generator Enabling Systematic Evaluations of Deep-Learning Architectures
Advances in deep learning and neural networks have resulted in the rapid...
research
∙
10/11/2019
Blink: Fast and Generic Collectives for Distributed ML
Model parameter synchronization across GPUs introduces high overheads fo...
research
∙
10/07/2019
Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization
Modern neural networks are increasingly bottlenecked by the limited capa...
research
∙
09/20/2019
NeuroVectorizer: End-to-End Vectorization with Deep Reinforcement Learning
One of the key challenges arising when compilers vectorize loops for tod...
research
∙
08/04/2019