Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Concept

Calcul hétérogène

Publications associées (30)

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

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 ...

2022

Dynamic SIMD Parallel Execution on GPU from High-Level Dataflow Synthesis

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

Developing and fine-tuning software programs for heterogeneous hardware such as CPU/GPU processing platforms comprise a highly complex endeavor that demands considerable time and effort of software engineers and requires evaluating various fundamental comp ...

MDPI2022

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

Mirjana Stojilovic, 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 ...

2022

Performance Estimation of High-Level Dataflow Program on Heterogeneous Platforms by Dynamic Network Execution

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

The performance of programs executed on heterogeneous parallel platforms largely depends on the design choices regarding how to partition the processing on the various different processing units. In other words, it depends on the assumptions and parameters ...

MDPI2022

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

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

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

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

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

Thermal and Voltage-Aware Performance Management of 3D MPSoCs with Flow Cell Arrays and Integrated SC Converters

David Atienza Alonso, Giovanni Ansaloni, Marina Zapater Sancho, Alexandre Sébastien Julien Levisse, Halima Najibi

Flow cell arrays (FCAs) concurrently provide efficient on-chip liquid cooling and electrochemical power generation. This technology is especially promising for three-dimensional multi-processor systems-on-chip (3D MPSoCs) realized in deeply scaled technolo ...

2022

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

David Atienza Alonso, Marina Zapater Sancho, Ali Pahlevan, Darong Huang, Luis Maria Costero Valero

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 ...

2022