INTERNATIONAL CONFERENCE ON ADVANCES IN
COMPUTING TECHNOLOGIES AND AI
10-14 July 2023, Istanbul
ABOUT CONFERENCE

"International Conference on advances in Computing and AI" brings both industry and academia leaders for the insights and discussion of technological advances, research results and applications in the fields of Artificial Intelligence Methods and Technologies as well as advanced computing algorithms. The conference will provide a valuable opportunity for researchers and industry experts to exchange their ideas face to face. We have the strong organization team, stable reputation and reliable sponsors all around the world.

OUR EXPERTS
  • LIU WEI

    Computing Industry Representative

  • STAS PAVLOV
    R&D Director in AI
  • STANISLAV MOISEEV
    R&D Team Leader
  • VITALY SLOBODSKOY
    Performance Analysis and Accelerators Team Leader
  • SERGEY GOLOLOBOV
    Math libraries team leader
  • DING ZHAOHUI
    Chief expert of cluster computing HPC
  • SHEVTCOV MAKSIM
    Head of memory acceleration technology center
  • ALEXANDER BOVYRIN
    AI Expert and Teacher

  • ANDREY DOBROV
    Compiler team leader
  • LIN TENGYI
    GPU chip planning expert of the computing product line
  • ANTON MALAKHOV
    Paraller Runtimes team leader
  • ZHOU BIN
    CTO of Huawei Ascend computing business and chief architect of Ascend computing
  • SUN HONGWEI
    Computing Foundation Software Senior Expert (Chief)
  • VADIM PISAREVSKY
    OpenCV architect
  • ZHOU YIGANG
    Senior Technical Planner for Computing Chips
VENUE 2023
ISTANBUL
Straddling many countries, Turkey is the bridge between Europe and Asia. 75 million people live there. Turkey has many cities with ancient history, and largest and arguably the most beautiful city is Istanbul. Constantinople was the name of Istanbul a long time ago. One on the most famous attractions in Istanbul , the Hagia Sophia what is mean Holy Wisdom from Greek language. It is a great architectural beauty and an important monument both for Byzantine and for Ottoman Empires. Once a church, later a mosque, and now a museum, people from Turkey consider Hagia Sophia to be one of their most precious landmarks.
MAIN TOPICS - ISTANBUL 2023
AI inference acceleration: AI -based algorithm for inference computing resource management
The new inference engine has an efficient and convenient API for deep learning model inference on accelerators. The challenges, opportunities, and learnings for generative inference on huge Transformer-based models (e.g. chatGPT) with tight latency limits and long sequence lengths are presented. An overview of AI projects and the challenges in delivering efficient pre- and post-processing algorithms to inference engine users will also be given.
AI + HPC: New approaches in HPC application and performance improvement




Accelerated computing allows researchers to achieve scientific breakthroughs more quickly, with the help of AI producing accurate results in a shorter timeframe. As a result, AI has been adopted in high-performance computing.




Large-scale graph computing: Open problems and research directions




This topic focuses on the analysis of large graphs. It provides an overview of the existing approaches to graph analysis and outlines open problems in the field. These include the use of linear-algebraic methods, tackling calculation problems on distributed clusters, dealing with the segmentation (partitioning) of graphs for sparse social networks, analyzing dynamic graphs, and more.



Parallel Algorithms, Concurrency, and optimization of parallel applications



The accuracy and performance of neural networks depend on established algorithms and data structures, as well as advanced counterparts commonly employed in machine learning. One can discover methods to enhance neural network speed, utilize graph algorithms in artificial intelligence, and more.

Mixed-precision iterative solvers and preconditioners for symmetric positive definite matrices


In the domain of classic high-performance computing (HPC), solving large systems of linear algebraic equations with sparse matrices is a significant challenge. Over the centuries, various direct and iterative methods have been created to tackle this problem. Math Library has implemented sparse solvers that overcome some of these challenges and will continue to address future challenges in this area.
Direct two-phase liquid spray chip cooling





Research on high heat density cooling solution in computing systems, which achieves very high dissipation efficiency on single-point heat sources. This cooling system will allow us to assemble a much more powerful chip and denser rack for exascale level HPC cluster.

2022
Dubai
DUBAI
Dubai - is commercial sector is not only one of the most modern in the world, it is also one of the fastest-growing business communities on the planet. A massive investment program has made Dubai and the Emirates in general one of the key business hotspots, with investors, entrepreneurs, and global brands eager to be a part of the progression.
MAIN TOPICS - DUBAI 2022
Application of advanced algorithms towards AI
The accuracy and performance of neural networks directly depends on well-known algorithms and data structures. In addition, their advanced counterparts are widely used in machine learning.
This topic is devoted to the approaches for accelerating the neural network performance, application of graph algorithms in artificial intelligence, and others.
Residue Number System
challenges
RNS can be used for efficient multiplication and addition which opens various ways for RNS applicability in AI and HPC (particularly through matrix multiplication). However, there are challenges to apply RNS for the floating point types: effective RNS scaling and comparison as well as conversion are needed to be implemented. The main target is trying to enable RNS for floating point matrix multiplication.
Exascale computing
challenges
Exascale supercomputers are our present, but development of Exascale-ready scalable applications is a big challenge as well. The research focus is on effective parallel runtimes and new parallel programming paradigms, performance analysis and characterization of exascale applications.
Large-scale graph computing: open problems and research directions
This topic is devoted to the problems of analysis of large graphs. An overview of current approaches to graph analysis and open problems in this field (linear-algebraic method, problems of calculations on a distributed cluster, problem of segmentation (partitioning) graph for sparse graphs of social networks type, analysis of dynamic graphs and others) will be presented .
Source Code Static Analysis:
state of the art
FDS task (Interprocedural, Finite, Distributive, Subsets) is well known compiler optimization technique which is applicable to sound, but not to precise source code static analysis. Evolution of symbolic execution methods applied to static inference of program execution facts can improve precision of program analysis.
This topic is devoted to an approach to program analysis which is both complete and precise and allows to detect security and stability problems in real-world projects in C and C++.
ARM-based CPU math
Seemingly simple concepts from linear algebra open the door to a wonderful world of high-performance computing (HPC). What does it take to make simple algorithms to perform on ARM-based architecture?
This topic is devoted to algorithmic challenges in dense & sparse linear solvers and eigensolvers. Enabling of exascale clusters with millions of cores, low precision (up to 16-bit) calculations and neural network usage to solve NP-complete problems are examples of the challenges to handle.
VENUE 2022
TO BE CONTINUED...

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