Publications related to Futures and promises

Babak Falsafi, Mathias Josef Payer, Yuanlong Li, Siddharth Gupta, Yunho Oh, Qingxuan Kang, Abhishek Bhattacharjee

Precise exceptions are a cornerstone of modern computing as they provide the abstraction of sequential instruction execution to programmers while accommodating microarchitectural optimizations. However, increasing compute capabilities in deep memory hierar ...

ACM2023

Learning Dynamics of Spring-Mass Models with Physics-Informed Graph Neural Networks

Olga Fink, Vinay Sharma, Manav Manav

We propose a physics-informed message-passing graph neural network (GNN) for learning the dynamics of springmass systems. The proposed method embeds the underlying physics directly into the message-passing scheme of the GNN. We compare the new scheme with ...

Research Publishing2023

A Comprehensive Timing Model for Accurate Frequency Tuning in Dataflow Circuits

Paolo Ienne, Andrea Guerrieri, Lana Josipovic, Carmine Rizzi

The ability of dataflow circuits to implement dynamic scheduling promises to overcome the conservatism of static scheduling techniques that high-level synthesis tools typically rely on. Yet, the same distributed control mechanism that allows dataflow circu ...

IEEE COMPUTER SOC2022

Inter-actions parallel execution on GPU from high-level dataflow synthesis

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

Recent GPU architectures make available numbers of parallel processing units that exceed by orders of magnitude the ones offered by CPU architectures. Whereas programs written using dataflow programming languages are well suited for programming heterogeneo ...

IEEE2022

Explicit Stabilized Multirate Method For Stiff Stochastic Differential Equations

Assyr Abdulle, Giacomo Rosilho De Souza

Stabilized explicit methods are particularly efficient, for large systems of stiff stochastic differential equations (SDEs) due to their extended stability domain. However, they lose their efficiency when a severe stiffness is induced by very few "fast" de ...

SIAM PUBLICATIONS2022

Fully-Asynchronous Fully-Implicit Variable-Order Variable-Timestep Simulation of Neural Networks

Felix Schürmann, Michael Lee Hines, Bruno Ricardo Da Cunha Magalhães

State-of-the-art simulations of detailed neurons follow the Bulk Synchronous Parallel execution model. Execution is divided in equidistant communication intervals, with parallel neurons interpolation and collective communication guiding synchronization. Su ...

2020

MATHICSE Technical Report : Explicit stabilized multirate method for stiff stochastic differential equations

Assyr Abdulle, Giacomo Rosilho De Souza

Stabilized explicit methods are particularly ecient for large systems of sti stochastic dif- ferential equations (SDEs) due to their extended stability domain. However, they loose their eciency when a severe stiness is induced by very few fast degrees of f ...

EPFL2020

Asynchronous Simulation of Neuronal Activity

Bruno Ricardo Da Cunha Magalhães

Simulations of the electrical activity of networks of morphologically-detailed neuron models allow for a better understanding of the brain. Short time to solution is critical in order to study long biological processes such as synaptic plasticity and learn ...

EPFL2019

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Futures and promises

DatAFLow: Toward a Data-flow-guided Fuzzer

Imprecise Store Exceptions

Learning Dynamics of Spring-Mass Models with Physics-Informed Graph Neural Networks

A Comprehensive Timing Model for Accurate Frequency Tuning in Dataflow Circuits

Inter-actions parallel execution on GPU from high-level dataflow synthesis

Explicit Stabilized Multirate Method For Stiff Stochastic Differential Equations

Fully-Asynchronous Fully-Implicit Variable-Order Variable-Timestep Simulation of Neural Networks

MATHICSE Technical Report : Explicit stabilized multirate method for stiff stochastic differential equations

Asynchronous Simulation of Neuronal Activity

Theory and Practice of Coroutines with Snapshots

Graph Chatbot

Chat with Graph Search

Learning Dynamics of Spring-Mass Models with Physics-Informed Graph Neural Networks

Asynchronous Simulation of Neuronal Activity

Imprecise Store Exceptions

Theory and Practice of Coroutines with Snapshots

Explicit Stabilized Multirate Method For Stiff Stochastic Differential Equations

DatAFLow: Toward a Data-flow-guided Fuzzer

A Comprehensive Timing Model for Accurate Frequency Tuning in Dataflow Circuits

Inter-actions parallel execution on GPU from high-level dataflow synthesis

Fully-Asynchronous Fully-Implicit Variable-Order Variable-Timestep Simulation of Neural Networks

MATHICSE Technical Report : Explicit stabilized multirate method for stiff stochastic differential equations