The MANGO FET-HPC Project: An Overview

Flich, José; Agosta, Giovanni; Ampletzer, Philipp; Alonso, David Atienza; Cilardo, Alessandro; Fornaciari, William; Kovač, Mario; Roudet, Fabrice; Zoni, Davide

doi:10.1109/cse.2015.57

Cited by 8 publications

(3 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…MANGO platform [15,16] is a heterogeneous highperformance computing system consisting of generalpurpose compute nodes (GN) that are intertwined with heterogeneous acceleration nodes (HN), linked by an across-boundary homogeneous interconnect. GNs are based on CPUs (i.e.…”

Section: Platform -Mango Platformmentioning

confidence: 99%

Performance-efficient integration and programming approach of DCT accelerator for HEVC in MANGO platform

2019

View full text Add to dashboard Cite

Video encoding based on novel HEVC standard is an extremely computationally expensive process and achieving efficient encoding requires intelligent utilization of all available resources, from both software and hardware perspective. Profiling and analysis of the encoding process identified Discrete cosine transform (DCT) as one of the key kernels that consume most of the time in the application's runtime. Therefore, high-throughput, fully-pipelined hardware accelerator was designed in FPGA and integrated into MANGO platform. MANGO platform is heterogeneous HPC system that consists of different types of nodes, from general purpose nodes (GN) to heterogeneous nodes (HN). While executing specific kernels on GN nodes is a straightforward process, executing kernels on accelerator-based HNs is a more complex procedure and requires specific integration to successfully exploit heterogeneous architecture. This paper presents performance-efficient integration of DCT hardware accelerator in MANGO platform, focusing on the performance of the encoder while maintaining coding efficiency and video quality of the encoded bitstream. Several approaches were considered, tested and compared; from the standalone integration where series of single tasks were offloaded to the DCT accelerator, to more complex solutions based on smart buffer utilization.

show abstract

Section: Platform -Mango Platformmentioning

confidence: 99%

Performance-efficient integration and programming approach of DCT accelerator for HEVC in MANGO platform

2019

View full text Add to dashboard Cite

show abstract

“…These emerging scenarios require that new HPC platforms are able to support multiple applications running concurrently, possibly with conflicting Quality of Service requirements [3][4][5][6][7]. In addition, at the technology level, RECIPE addresses deep heterogeneity, based on dedicated accelerators like GPUs and FPGAs, as an enabling factor for improved energy efficiency, building on the results collected from previous research projects [8,9].…”

Section: Introduction and Long-term Objectivesmentioning

confidence: 99%

The RECIPE approach to challenges in deeply heterogeneous high performance systems

Agosta

Fornaciari

Atienza

et al. 2020

Microprocessors and Microsystems

Self Cite

View full text Add to dashboard Cite

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

show abstract

“…It is worth noting that the convergence between embedded and high performance computing systems, driven by the need to contain the power budget of high performance computing systems on one hand, and by the increased amount of functionalities requested from embedded and mobile systems, is leading to a computing continuum where established techniques from once separate domains are being adopted across larger portions of the continuum. Thus, clustered architectures not unlike the Explicitly Managed Many Cores are investigated as accelerators in the high-performance computing domain [5].…”

Section: Introductionmentioning

confidence: 99%

Stack size estimation on machine-independent intermediate code for OpenCL kernels

Cherubin

Scandale

Agosta

2016

Proceedings of the 7th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and the

Self Cite

View full text Add to dashboard Cite

Stack size is an important factor in the mapping decision when dealing with embedded heterogeneous architectures, where fast memory is a scarce resource. Trying to map a kernel onto a device with insufficient memory may lead to reduced performance or even failure to run the kernel. OpenCL kernels are often compiled just-intime, starting from the source code or an intermediate machineindependent representation. Precise stack size information, however, is only available in machine-dependent code. We provide a method for computing the stack size with sufficient accuracy on machine-independent code, given knowledge of the target ABI and register file architecture. This method can be applied to make mapping decisions early, thus avoiding to compile multiple times the code for each possible accelerator in a complex embedded heterogeneous system.

show abstract

The MANGO FET-HPC Project: An Overview

Cited by 8 publications

References 15 publications

Performance-efficient integration and programming approach of DCT accelerator for HEVC in MANGO platform

Performance-efficient integration and programming approach of DCT accelerator for HEVC in MANGO platform

The RECIPE approach to challenges in deeply heterogeneous high performance systems

Stack size estimation on machine-independent intermediate code for OpenCL kernels

Contact Info

Product

Resources

About