Publication

Way Stealing: Cache-assisted Automatic Instruction Set Extensions

Related publications (30)

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As a unified data repository, data lake plays a vital role in enterprise data management and analysis. It composes the raw files into tables that are processed in-situ by various computation engines and applications. Therefore, the read performance of the ...

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DFAulted: Analyzing and Exploiting CPU Software Faults Caused by FPGA-Driven Undervolting Attacks

Mirjana Stojilovic, David Dervishi, Dina Gamaleldin Ahmed Shawky Mahmoud

Field-programmable gate arrays (FPGAs) combine hardware reconfigurability with a high degree of parallelism. Consequently, FPGAs offer performance gains and power savings for many applications. A recent trend has been to leverage the hardware versatility o ...

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Beating the I/O Bottleneck: A Case for Log-Structured Virtual Disks

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With the increasing dominance of SSDs for local storage, today's network mounted virtual disks can no longer offer competitive performance. We propose a Log-Structured Virtual Disk (LSVD) that couples log-structured approaches at both the cache and storage ...

ASSOC COMPUTING MACHINERY2022

Reinforcement Learning-Based Joint Reliability and Performance Optimization for Hybrid-Cache Computing Servers

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Computing servers play a key role in the development and process of emerging compute-intensive applications in recent years. However, they need to operate efficiently from an energy perspective viewpoint, while maximizing the performance and lifetime of th ...

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FPGA-to-CPU Undervolting Attacks

Mirjana Stojilovic, Dina Gamaleldin Ahmed Shawky Mahmoud

FPGAs are proving useful and attractive for many applications, thanks to their hardware reconfigurability, low power, and high-degree of parallelism. As a result, modern embedded systems are often based on systems-on-chip (SoCs), where CPUs and FPGAs share ...

IEEE2022

Structured and tiled-based pruning of Deep Learning models targeting FPGA implementations

Alexandre Schmid, Lizeth Gonzalez Carabarin

Model compression techniques have lead to a reduction of size and number of computations of Deep Learning models. However, techniques such as pruning mostly lack of a real co-optimization with hardware platforms. For instance, implementing unstructured pru ...

IEEE2022

Electrical-Level Attacks on CPUs, FPGAs, and GPUs: Survey and Implications in the Heterogeneous Era

Mirjana Stojilovic, Dina Gamaleldin Ahmed Shawky Mahmoud

Given the need for efficient high-performance computing, computer architectures combining CPUs, GPUs, and FPGAs are nowadays prevalent. However, each of these components suffers from electrical-level security risks. Moving to heterogeneous systems, with th ...

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Hardware and Software Support for RPC-Centric Server Architecture

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Online services have become ubiquitous in technological society, the global demand for which has driven enterprises to construct gigantic datacenters that run their software. Such facilities have also recently become a substrate for third-party organizatio ...

EPFL2022

Micro-architectural Analysis of Database Workloads

Utku Sirin

Database workloads have significantly evolved in the past twenty years. Traditional database systems that are mainly used to serve Online Transactional Processing (OLTP) workloads evolved into specialized database systems that are optimized for particular ...

EPFL2021

Rebooting Virtual Memory with Midgard

Babak Falsafi, Atri Bhattacharyya, Siddharth Gupta, Mathias Josef Payer, Yunho Oh, Abhishek Bhattacharjee

Computer systems designers are building cache hierarchies with higher capacity to capture the ever-increasing working sets of modern workloads. Cache hierarchies with higher capacity improve system performance but shift the performance bottleneck to addres ...

2021