In Quattro and POLIMI testing the new two-phase cooling system.

In Quattro and Politecnico di Milano are collecting experimental data at HEAP Lab in March 23-24. The goal is to build the thermal model of the two-phase cooling systems. The thermal test chip developed by POLIMI and the (portable) prototype of the two-phase cooling systems have been integrated to simulate the thermal behavior of a real processor.

A first step towards a real in-field validation!

In Quattro: Giorgia Rancione, Luca Saraceno
Politecnico di Milano: William Fornaciari and Federico Terraneo


MathLib: Colella’s Dwarves

Mathematical libraries are a key component of the software stack for exascale-class applications. As a matter of fact, exascale computing deployment is conditioned by the development of new suitable numerical algorithms, since most of existing ones are not able to face many issues raising into the race to exascale.
Mathematical libraries provide building-blocks implementing up-to-date methods and algorithms that application developers can reuse in form of highly-reliable and high-performance components.

Any new generation of computer architectures brings new challenges to achieve high performance mathematical solvers and a bi-directional interaction between new computer architectures/environments and new mathematical software is ever more crucial for deployment and effective use of the new technology to advance in Science, Industry and Society.

The need to improve computing performance in the near and medium term indicates that exascale and also post-exascale platforms will continue to emphasize heterogeneity. This type of architecture exploits at node level, accelerators such as modern GPUs and reconfigurable hardware such as FPGA to boost performance and also energy efficiency in computations. As computer architectures become heterogeneous, there is the need for algorithms that support mixed-precision and minimize communications among the different devices and memory levels. The new power-to-solution metrics requires a rethinking of many computational kernels of HPC applications looking for the best trade-off between the reduction of the energy consumption and the minimization of the time-to-solution, promoting reproducibility and scalability.

We will provide new high-performance algorithms and software modules for some of the so-called Colella’s dwarves, who identified numerical methods crucial for science and engineering. In particular, we will focus on algorithms and software for sparse linear algebra, where data sets include many zero-values and are usually stored in compressed data structures to reduce storage and memory bandwidth requirements,hey are generally accessed with indexed loads and stores, and main computational kernels are communication bound.

The library kernels will be of immediate use in a wide range of applications, ranging from classical scientific simulation to AI techniques, including automatic pattern recognition in complex systems, and will be tested in some of the applications proposed as use cases in this project.

Leading Partner: CNR


The TEXTAROSSA Co-Design Approach


Supercomputing offers access to enormous amounts of computational power that are needed by many applications in different scientific and industrial sectors. Public services such as weather predictions require such capabilities, as do critical industries like Oil \& Gas (for fuel deposit discovery) and Pharmaceutical (for drug design). Scientific discoveries in fields such as quantum physics or high energy physics are also made possible by supercomputers.

However, increasingly powerful supercomputers are hitting a ceiling imposed by the ability to provide (and sustain) electrical power through the grid. To avoid this limitation, supercomputing hardware designers need to rely on systems that are less power-hungry, but more difficult for application designers to effectively use, due to characteristics such as heterogeneity (that is, the use of processing elements different from the typical “processor” that is commonly found also in laptop and desktop personal computers) and reconfigurability (that is, the use of systems whose functions are programmable at the hardware rather than software level).

TEXTAROSSA Contributions

TEXTAROSSA aims at making the advantages of reconfigurable hardware and associated technical advances available to application developers by means of a co-design approach.
Whereas in standard supercomputing application design, the hardware is given, and the application developer works only at creating the software application, in co-design, hardware and software are designed together, at least in part.

TEXTAROSSA will leverage co-design, which was first developed in the context of embedded systems, through a new Integrated Development Vehicle, a hardware-software platform for supercomputing including reconfigurable hardware elements. TEXTAROSSA aims at providing tools that will help the application developer in designing and implementing the application on this type of platform, semi-automatically performing the tasks of deciding which activities will be performed on the reconfigurable hardware, and producing optimized hardware accelerators for those activities.


European High Performance Computing Joint Undertaking Workshop

The Tuscany Region of Italy via TOUR4EU organized at Bruxelles a workshop entitled “European High Performance Computing Joint Undertaking Workshop” in which prof. Aldinucci and prof. Saponara presented the current EU projects, including TEXTAROSSA. Please find the workshop report here (in Italian).


TEXTAROSSA hiring: position open at INRIA

PhD Position F/M Optimization of high-performance applications on heterogeneous computing nodes

A PhD position is open in HiePACS, a joint project-team with Bordeaux INP, Bordeaux University and CNRS, and CAMUS, a joint project-team with Strasbourg University and CNRS.

The purpose of the HiePACS project is to efficiently perform frontier simulations arising from challenging research and industrial multiscale applications. The solution of these challenging problems requires a multidisciplinary approach involving applied mathematics, computational and computer sciences. In applied mathematics, it essentially involves advanced numerical schemes. In computational science, it involves massively parallel computing and the design of highly scalable algorithms and codes to be executed on future petaflop (and beyond) platforms. Through this approach, HiePACS intends to contribute to all steps that go from the design of new high-performance more scalable, robust and more accurate numerical schemes to the optimized implementations of the associated algorithms and codes on very high performance supercomputers.

The CAMUS research team focuses on parallelization, optimization, profiling, modeling, and compilation. The team has increasing interests in the approaches used and enhanced in the high-performance community. The team’s research activities are organized into five main issues that are closely related to reach the following objectives: performance, correction and productivity. These issues are: static parallelization and optimization of programs (where all statically detected parallelisms are expressed as well as all “hypothetical” parallelisms which would be eventually taken advantage of at runtime), profiling and execution behavior modeling (where expressive representation models of the program execution behavior will be used as engines for dynamic parallelizing processes), dynamic parallelization and optimization of programs (such transformation processes running inside a virtual machine), object-oriented programming and compiling for multicores (where object parallelism, expressed or detected, has to result in efficient runs), and finally program transformations proof (where the correction of many static and dynamic program transformations has to be ensured).

The objectives of the thesis will be to study how the new features of the TEXTAROSSA computing nodes can be used to develop high performance applications. With this aim, we will study how high performance task-based applications can be adapted in order to exploit the full potential of the platform. We will thus consider two existing high performance libraries by adapting them, designing advanced scheduling strategies and considering energy consumption awareness as a major constraint of the work.

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Press Release

TEXTAROSSA, a project co-funded by the European High Performance Computing (EuroHPC) Joint Undertaking, kicked off on April 1st to drive innovation in efficiency and usability of high-end HPC systems.

TEXTAROSSA (Towards EXtreme scale Technologies and AcceleRatOrS for HW/SW Supercomputing Applications for exascale) is funded by the European High Performance Computing (EuroHPC) Joint Undertaking within the EuroHPC-01-2019/Extreme scale computing and data driven technologies. The three-year project, led by ENEA (Italy), aggregates 17 institutions and companies located in 5 European countries (Italy, France, Poland, Germany and Spain).
The TEXTAROSSA project aims to achieve a broad impact on the High Performance Computing (HPC) field both in pre-exascale and exascale scenarios. The TEXTAROSSA consortium will develop new hardware accelerators, innovative two-phase cooling equipment, advanced algorithms, methods and software products. The developed technologies will be tested on the Integrated Development Vehicles (IDV) mirroring and extending the European Processor Initiative’s ARM64-based architecture, and on an OpenSequana testbed. To drive the technology development and assess the impact of the proposed innovations from node to system levels, TEXTAROSSA will use a selected but representative number of HPC, HPDA and AI applications covering challenging HPC domains such as general-purpose numerical kernels, High Energy Physics (HEP), Oil & Gas, climate modelling, as well as emerging domains such as High Performance Data Analytics (HPDA) and High Performance Artificial Intelligence (HPC-AI).

Read the full press release.



Welcome to the TEXTAROSSA project website!