Publications associées à Advanced Micro Devices

Rebooting Virtual Memory with Midgard

Virtual Memory (VM) is a critical programming abstraction that is widely used in various modern computing platforms. With the rise of datacenter computing and birth of planet-scale online services, the semantic and capacity requirements from memory have ev ...

EPFL2023

X-HEEP: An Open-Source, Configurable and Extendible RISC-V Microcontroller

David Atienza Alonso, Miguel Peon Quiros, José Angel Miranda Calero, Simone Machetti, Pasquale Davide Schiavone, Thomas Christoph Müller, Rubén Rodríguez Álvarez, Benoît Walter Denkinger, Ruben Rodriguez, Saverio Nasturzio

In this work, we present eXtendible Heterogeneous Energy-Efficient Platform (X-HEEP), a configurable and extendible single-core RISC-V-based ultra-low-power microcontroller. X-HEEP can be used standalone as a low-cost microcontroller, or it can be integrat ...

New York2023

Effective Inhibition of TDP-43 Aggregation by Native State Stabilization

Hilal Lashuel, Yllza Jasiqi, Lixin Yang

Preventing the misfolding or aggregation of transactive response DNA binding protein with 43 kDa (TDP-43) is the most actively pursued disease-modifying strategy to treat amyotrophic lateral sclerosis and other neurodegenerative diseases. In this work, we ...

Wiley-VCH Verlag GmbH2024

Efficient Analytical Query Processing on CPU-GPU Hardware Platforms

Periklis Chrysogelos

Timely insights lead to business growth and scientific breakthroughs but require analytical engines that cope with the ever-increasing data processing needs. Analytical engines relied on rapid CPU improvements, yet the end of Dennard scaling stopped the fr ...

EPFL2022

SIMD Parallel Execution on GPU from High-Level Dataflow Synthesis

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

Writing and optimizing application software for heterogeneous platforms including GPU units is a very difficult task that requires designer efforts and resources to consider several key elements to obtain good performance. Dataflow programming has shown to ...

2022

Performance Estimation of High-Level Dataflow Program on Heterogeneous Platforms

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

The performance of programs written in languages following the dataflow model of computation (MoC) largely depends on the configuration (partitioning, mapping, scheduling, buffer dimensioning) chosen during the synthesis stages. Furthermore, this programmi ...

2022

Full System Exploration of On-Chip Wireless Communication on Many-Core Architectures

David Atienza Alonso, Marina Zapater Sancho, Giovanni Ansaloni, Rafael Medina Morillas, Yasir Mahmood Qureshi, Joshua Alexander Harrison Klein

In order to develop sustainable and more powerful information technology (IT) infrastructures, the challenges posed by the "memory wall" are critical for the design of high-performance and high-efficiency many-core computing systems. In this context, recen ...

IEEE2022

Integration of MEMS in Silicon Photonics

Alain Yuji Takabayashi

Like integrated electronics, integrated photonics such as Silicon Photonics benefit from increased device-density on a single chip. Silicon is an excellent material for integrated photonics because its high refractive index allows devices to be made small, ...

EPFL2021

High-Speed ADC Design and Optimization for Wireline Links

Ayça Akkaya

The ever-growing global internet traffic has increased demand for higher speed data transmission. As the bandwidth requirements of wireline links increase, extensive digital equalization techniques are required to compensate for the high-frequency channel ...

EPFL2021

Micro-architectural Analysis of OLAP: Limitations and Opportunities

Anastasia Ailamaki, Utku Sirin

Understanding micro-architectural behavior is important for efficiently using hardware resources. Recent work has shown that in-memory online transaction processing (OLTP) systems severely underutilize their core micro-architecture resources [29]. Whereas, ...

ASSOC COMPUTING MACHINERY2020