Publications associées à Instruction-level parallelism

X-Attack 2.0: The Risk of Power Wasters and Satisfiability Don’t-Care Hardware Trojans to Shared Cloud FPGAs

Mirjana Stojilovic, Dina Gamaleldin Ahmed Shawky Mahmoud, Beatrice Shokry Samir Shokry, Wei Hu

Cloud computing environments increasingly provision field-programmable gate arrays (FPGAs) for their programmability and hardware-level parallelism. While FPGAs are typically used by one tenant at a time, multitenant schemes supporting spatial sharing of c ...

2024

Imprecise Store Exceptions

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

FISHFUZZ: Catch Deeper Bugs by Throwing Larger Nets

Mathias Josef Payer, Flavio Toffalini, Han Zheng, Yuqing Zhang, Jiayuan Zhang

Fuzzers effectively explore programs to discover bugs. Greybox fuzzers mutate seed inputs and observe their execution. Whenever a seed reaches new behavior (e.g., new code or higher execution frequency), it is stored for further mutation. Greybox fuzzers d ...

Usenix Assoc2023

A 16-bit Floating-Point Near-SRAM Architecture for Low-power Sparse Matrix-Vector Multiplication

David Atienza Alonso, Giovanni Ansaloni, Grégoire Axel Eggermann, Marco Antonio Rios

State-of-the-art Artificial Intelligence (AI) algorithms, such as graph neural networks and recommendation systems, require floating-point computation of very large matrix multiplications over sparse data. Their execution in resource-constrained scenarios, ...

New York2023

Improving K-means Clustering Using Speculation

Anastasia Ailamaki, Viktor Sanca, Eleni Zapridou, Stefan Igescu

K-means is one of the fundamental unsupervised data clustering and machine learning methods. It has been well studied over the years: parallelized, approximated, and optimized for different cases and applications. With increasingly higher parallelism leadi ...

2023

Unleashing Parallelism in Elastic Circuits with Faster Token Delivery

Paolo Ienne, Andrea Guerrieri, Lana Josipovic, Ayatallah Ahmed Gamal Kamal Elakhras

High-level synthesis (HLS) is the process of automatically generating circuits out of high-level language descriptions. Previous research has shown that dynamically scheduled HLS through elastic circuit generation is successful at exploiting parallelism in ...

IEEE COMPUTER SOC2022

Real-Time Nonlinear Model Predictive Control for Fast Mechatronic Systems

Petr Listov

This thesis presents an efficient and extensible numerical software framework for real-time model-based control. We are motivated by complex and challenging mechatronic applications spanning from flight control of fixed-wing aircraft and thrust vector cont ...

EPFL2022

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

Do Children Adapt Their Perspective to a Robot When They Fail to Complete a Task?

Pierre Dillenbourg, Elmira Yadollahi, Ana Paiva

Spatial understanding and communication are essential skills in human interaction. An adequate understanding of others' spatial perspectives can increase the quality of the interaction, both perceptually and cognitively. In this paper, we take the first st ...

Assoc Computing Machinery2022

From C/C plus plus Code to High-Performance Dataflow Circuits

Paolo Ienne, Andrea Guerrieri, Lana Josipovic

High-level synthesis (HLS) tools typically generate statically scheduled datapaths. Static scheduling implies that the resulting circuits have a hard time exploiting parallelism in code with potential memory dependences, with control dependences, or where ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022