Giuseppe MassariPolitecnico di Milano | Polimi · Department of Electronics, Information, and Bioengineering
Giuseppe Massari
PhD Computer Engineering
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61
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Introduction
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October 2011 - present
Publications
Publications (61)
NIST is conducting a process for the standardization of post-quantum cryptosystems, i.e., cryptosys-tems that are resistant to attacks by both traditional and quantum computers and that can thus substitute the traditional public-key cryptography solutions which are expected to be broken by quantum computers in the next decades. This manuscript prov...
Since its introduction in 2017, the Posit™ format for representing real numbers has attracted a lot of interest, as an alternative to IEEE 754 floating point representation. Several hardware implementations of arithmetic operations between posit numbers have also been proposed in recent years.
In this work, we analyze the dynamic power consumption...
In the near future, Exascale systems will need to bridge three technology gaps to achieve high performance while remaining under tight power constraints: energy efficiency and thermal control; extreme computation efficiency via HW acceleration and new arithmetic; methods and tools for seamless integration of reconfigurable accelerators in heterogen...
To achieve high performance and high energy efficiency
on near-future exascale computing systems, three key
technology gaps needs to be bridged. These gaps include: energy
efficiency and thermal control; extreme computation efficiency
via HW acceleration and new arithmetics; methods and
tools for seamless integration of reconfigurable accelerators...
RECIPE (REliable power and time-ConstraInts-aware Predictive management of heterogeneous Exascale systems) is a recently started project funded within the H2020 FETHPC programme, which is expressly targeted at exploring new High-Performance Computing (HPC) technologies. RECIPE aims at introducing a hierarchical runtime resource management infrastru...
Application requirements in High-Performance Computing (HPC) are becoming increasingly exacting, and the demand for computational resources is rising. In parallel, new application domains are emerging, as well as additional requirements, such as meeting real-time constraints. This requirement, typical of embedded systems, is difficult to guarantee...
Performance and power constraints come together with Complementary Metal Oxide Semiconductor technology scaling in future Exascale systems. Technology scaling makes each individual transistor more prone to faults and, due to the exponential increase in the number of devices per chip, to higher system fault rates. Consequently, High-performance Comp...
Heterogeneous computing is a promising solution to scale the performance of computing systems maintaining energy and power efficiency. Managing such resources is, however, complex and it requires smart resource allocation strategies in both embedded and high-performance systems. In this short paper, we propose a game theory approach to allocate het...
Energy efficiency and thermal management have become major concerns in both embedded and HPC systems. The progress of silicon technology and the subsequent growth of the dark silicon phenomena are negatively affecting the reliability of computing systems. As a result, in the next future we expect run-time variability to increase in terms of both pe...
RECIPE (REliable power and time-ConstraInts-aware Predictive management of heterogeneous Exascale systems) is a recently started project funded within the H2020 FETHPC programme, which is expressly targeted at exploring new High-Performance Computing (HPC) technologies. RECIPE aims at introducing a hierarchical runtime resource management infrastru...
High-Performance Computing (HPC) is rapidly moving towards the adoption of nodes characterized by an heterogeneous set of processing resources. This has already shown benefits in terms of both performance and energy efficiency. On the other side, heterogeneous systems are challenging from the application development and the resource management pers...
In battery-powered embedded systems, the energy budget management is a critical aspect. For systems using unreliable power sources, e.g. solar panels, the continuous system operation is a challenging requirement. In such scenarios, effective management policies must rely on accurate energy estimations. In this paper we propose a measurement-based p...
High-Performance Computing (HPC) is rapidly moving towards the adoption of nodes characterized by an heterogeneous set of processing resources. This has already shown benefits in terms of both performance and energy efficiency. On the other side, heterogeneous systems are challenging from the application development and the resource management pers...
The interest in probabilistic real-time is increasing, in response to the lack of traditional static WCET analysis methods for applications running on complex systems, like multi/many-cores and COTS platforms. However, the probabilistic theory is still immature and, furthermore, it requires strong guarantees on the timing traces, in order to provid...
This paper presents the statistical power estimation of goodness-of-fit tests for Extreme Value Theory (EVT) distributions. The presented dataset provides quantitative information on the statistical power, in order to enable the sample size selection in external validation scenario. In particular, high precision estimations of the statistical power...
The increasing functional and nonfunctional requirements of real-time applications, the advent of mixed criticality computing, and the necessity of reducing costs are leading to an increase in the interest for employing COTS hardware in real-time domains. In this scenario, the Linux kernel is emerging as a valuable solution on the software side, th...
This chapter is centered around uncertainty computation with on-demand resource allocation for run-off prediction in a High-Performance Computer environment. Our research stands on a runtime operating system that automatically adapts resource allocation with the computation to provide precise outcomes before the time deadline. In our case, input da...
The extreme integration levels reached by the silicon manufacturing process allowed the design of high-performance multi-core processors that meet the ever-increasing requirements of software applications. Unfortunately, we are living in the post Dennard’ scaling era, which is characterized by an increasing on-chip power density. This is pushing th...
This chapter focuses on a real-world application of HARPA in the embedded system domain. In particular, the application consists in bringing intelligence to the field of landslide and rockwall/rockfall monitoring by creating a battery-powered smart bridge for the Beesper network able to process data remotely, using machine learning and artificial i...
The goal of the HARPA solution is to overcome the performance variability (PV) by enabling next-generation embedded and high-performance platforms using heterogeneous many-core processors to provide cost-effectively dependable performance: the correct functionality and (where needed) timing guarantees throughout the expected lifetime of a platform....
Measurement-Based Probabilistic Timing Analysis, a probabilistic real-time computing method, is based on the Extreme Value Theory (EVT), a statistical theory applied to Worst-Case Execution Time analysis on real-time embedded systems. The output of the EVT theory is a statistical distribution, in the form of Generalized Extreme Value Distribution o...
The increasing pervasiveness of mobile and embedded devices (IoT/Edge), combined with the access to Cloud infrastructures, makes it possible to build scalable distributed systems, characterized by a multi-dimensional architecture. The overall picture is a massive collection of computing devices, characterized by very heterogeneous levels of perform...
The rapid advance of computer architectures towards more powerful, but also more complex platforms, has the side effect of making the timing analysis of applications a challenging task (Cullmann et al., 2010). The increasing demand of computational power in
cyber-physical systems (CPS) is getting hard to fulfill, if we consider typical real-time
co...
The transition to Exascale computing is going to be characterised by an increased range of application classes. In addition to traditional massively parallel "number crunching" applications, new classes are emerging such as real-time HPC and data-intensive scalable computing. Furthermore, Exascale computing is characterised by a "democratisation" o...
The Horizon 2020 MANGO project aims at exploring deeply heterogeneous accelerators for use in High-Performance Computing systems running multiple applications with different Quality of Service (QoS) levels. The main goal of the project is to exploit customization to adapt computing resources to reach the desired QoS. For this purpose, it explores d...
The increasing complexity of computing architectures is pushing for novel Dynamic Thermal Management (DTM) techniques. Accordingly, more accurate power and thermal models are required. In this work, we propose a thermal controller based on a constrained extremum-seeking algorithm, enabling resource allocation optimization under specific thermal con...
To sustain performance while facing always tighter power and energy envelopes, High Performance Computing (HPC) is increasingly leveraging heterogeneous architectures. This poses new challenges: to efficiently exploit the available resources, both in terms of hardware and energy, resource management must support a wide range of different heterogene...
The increasing pervasiveness of mobile devices combined with their replacement rate, led us to deal with the disposal of an increasing amount of still working electronic devices. This work proposes an approach to mitigate this problem by extending the mobile devices' lifetime, by integrating them as part of a distributed mobile computing system. Th...
This article is centred on a mathematical weather forecasting model that must run regularly (i.e. 24/7) on an HPC system. Depending on the environmental conditions, each execution of the model may have a different deadline and a different accuracy requirement. In order to minimize power consumption and heat, we minimize resource allocation as far a...
This paper introduces the mig framework: an Open MPI extension to transparently support the migration of application processes, over different nodes of a distributed High-Performance Computing (HPC) system. The framework provides mechanism on top of which suitable resource managers can implement policies to react to hardware faults, address perform...
An increasing number of High-Performance Applications demand some form of time predictability, in particular in scenarios where correctness depends on both performance and timing requirements, and the failure to meet either of them is critical. Consequently, a more predictable HPC system is required, particularly for an emerging class of adaptive r...
Single-ISA heterogeneous multi-core processors trade-off power with performance; however, threads that corun on shared resources suffer from resource contention, which induces performance degradation and energy inefficiency. The authors introduce a novel approach to optimise the co-scheduling of multi-threaded applications onheterogeneous processor...
In this paper, we propose a safety-critical system with a run-time resource management that is used to operate an application for flood monitoring and prediction. This application can run with different Quality of Service (QoS) levels depending on the current hydrometeorological situation. The system operation can follow two main scenarios - standa...
The extremely high technology process reached by silicon manufacturing (smaller than 32nm) has led to production of computational platforms and SoC, featuring a considerable amount of resources. Whereas from one side such multi- and many-core platforms show growing performance capabilities, from the other side they are more and more affected by pow...
Power consumption is a critical consideration in high performance computing
systems and it is becoming the limiting factor to build and operate Petascale
and Exascale systems. When studying the power consumption of existing systems
running HPC workloads, we find that power, energy and performance are closely
related which leads to the possibility t...
The silicon technology continues reducing scale following the Moore's law. Device variability increases due to a lost in controllability during silicon chip fabrication. The current methodologies based on error detection and thread re-execution (roll back) cannot be enough, when the number of errors increase and arrive to a threshold. This dynamic...
To support adaptivity of data parallel applications on multi-core platforms, we propose a framework based on the combination of OpenCL application auto-tuning and run-time resource management. The framework addresses computationally intensive multimedia OpenCL applications. For these target applications, we show that application auto-tuning, based...
To better exploit the capabilities offered by multi-core high-end embedded systems, new parallel programming paradigms, such as OpenCL, combined with effective resource management should be adopted. However, dealing with mixed workloads and time varying scenarios is still an open problem. This paper addresses such challenges by exploiting the syner...
Since the silicon technology entered the many-core era, new computing platforms are exploiting higher and higher levels of parallelism. Thanks to scalable, clustered architectures, embedded systems and high-performance computing (HPC) are rapidly converging.We are also experiencing a rapid overlapping of the challenges related to efficient exploita...
From Mobile to High-Performance Computing (HPC) systems, performance and energy efficiency are becoming always more challenging requirements. In this regard, heterogeneous systems, made by a general-purpose processor and one or more hardware accelerators, are emerging as affordable solutions. However, the effective exploitation of such platforms re...
Mainstream multicore architectures allow the execution of mixed workloads where multiple parallel applications run concurrently competing on shared computational resources. As different applications exhibit different and time varying resources needs, a suitable allocation policy is required to properly select and map resources at run-time on demand...
Emerging multi/many-core architectures, targeting both High Performance Computing (HPC) and mobile devices, increase the interest for self-adaptive systems, where both applications and computational resources could smoothly adapt to the changing of the working conditions. In these scenarios, an efficient Run-Time Resource Manager (RTRM) framework c...