American scientist JackDongarra won the Turing Award, the award's gold how? Here we are to address this issue for some discussion, I hope these contents can help friends in need.
The American Computer Society (ACM) will be the 2021 Turing Award to the United States of America University of Tennessee Department of Electrical Engineering and Computer Science Distinguished Professor, this year has been 71 years of age, JackJ.Dongarra, for his pioneering dedication to the level of scalar optimization algorithms and specialized tool libraries, so that high-performance computing cell phone software can keep pace with more than four decades of exponential hardware configuration improvements.
Dongarra's computational methods and cellular software have contributed to the development of high-performance computing trends and have been a significant hazard to several computational science industries, from artificial intelligence techniques to computerized image processing, according to ACM details.
Turing Award is the American Computer Society in 1966 to open the honorary award, is committed to rewarding the work of the computer has made major contributions to the person, known as "the Nobel Prize of the computer world". The Turing Award prize of 1 million dollars, by Google to provide financial support. The prize is named after Alan M. Turing, a British mathematician who demonstrated the mathematics and limits underlying computing.
Jack J. Dongarra, born July 18, 1950, received a bachelor's certificate in mathematics from Chicago State University in 1972; a master's degree in computer science from the Illinois Institute of Technology in 1973; and a Ph.D. in applied mathematics from the University of New Mexico in 1980, under the tutelage of Matlab founder and National Academy of Engineering engineering
Dongarra has been a Distinguished Professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee since 1989, and a member of the Outstanding Scientific Research Staff in the Computer Science and Mathematics Division at Oak Ridge National Laboratory. Since 2007, he has also been a Turing Fellow at the University of Manchester, UK, and an Adjunct Specialist Professor in the Department of Computer Science at Rice University.
Dongarra has received several awards during his research career, including the IEEE Pioneer in Computing Award, the SIAM/ACM Computational Science and Engineering Program Award, and the ACM/IEEE Kennedy Award. He is a Fellow of the ACM, the Institute of Electrical and Electronics Engineers (IEEE), the Society for Industrial and Applied Mathematics (SIAM), the American Association for the Advancement of Science (AAAS), the International Supercomputing Conference (ISC), and the International Electrotechnical Institute (IETI), in addition to being a Fellow of the Engineering Academy of the U.S. National Academy of Engineering, and a foreign vip member of the Royal Society.
Dongarra has advanced high-performance computing globally based on his dedication to efficient scalar optimization algorithms for linear generation computing, parallel processing computing programming regimes, and performance rating equipment. For nearly four decades, Moore's Law has led to exponential growth in the performance of hardware configurations. At the same stage, while most cell phone software has been unable to keep pace with this hardware configuration development, high-performance scalar cell phone software has done well, thanks in large part to Dongarra's optimization algorithms, development techniques, and manufacturing-quality software implementations.
This dedication establishes an architecture in which scientists and technical engineers have been able to make key discoveries and change the rules for autonomous innovation in industries such as data analytics, healthcare, renewable energy, weather trends, molecular biology, and socio-economics. dongarra's work has also been instrumental in advancing leaps and bounds in the architecture of computer systems, and applying the computer graphic processing and deep learning revolution in computer graphics processing and deep learning.
Dongarra's key contributions also include the creation of open source project libraries and specifications, which use lineage as the middle language expression, and can be used by a wide variety of applications. The library is written for single CPUs, parallel processing computers, multi-core nodes, and several GPUs per node. The library also introduces a number of key in-house innovations, including fully-automated adjustments, mixing and precision arithmetic, and batch command calculations.
Being a pioneer in high-performance computing, Dongarra has led the industry in persuading hardware configuration dealers to enhance this manner and cellular software developers to work with his open-source system libraries as an overarching goal. Finally, from laptops to the world's faster very computers, Dongarra's diligence has led to a line of generational software libraries that are widely used in high-performance scientific and engineering project calculations. Such libraries are especially important for the future of the industry, enabling ever more powerful computers to tackle challenging computational problems.
Gabriele Kotsis, the current president of the ACM, said, "Today's faster, very fast computers are making headlines in the news media and piquing the public's interest based on the astonishing feat of performing trillions of calculations in a second. But beyond the interest in record-breaking, high-performance computing (HPC) has been the premier specialized tool for scientific discovery, and HPC innovations have poured into many different computing industries, contributing to trends across all of them. jack Dongarra has been instrumental in guiding successful trends in this area. His pioneering work dates back to 1979, and he remains one of the most important and active managers in the HPC community. His career development undoubtedly demonstrates the Turing Award's recognition of 'outstanding contributions of lasting necessity'."
Jeff Dean, senior researcher at Google and senior vice president of Google Scientific Research and Google Mind and Body, said, "JackDongarra's work has changed and fueled the trends in scientific computing at the source. His deep work on the key to the world's most frequently used scalar repository is fundamental to all walks of scientific computing, helping to drive trends in industries ranging from drug discovery to weather forecasting, aerospace engineering, and dozens of others, helping to drive trends in industries ranging from drug discovery to weather forecasting, aerospace engineering, and dozens of others. His dedication to performing universal computers has long produced important developments for computer system architecture, (making it) particularly suited to scalar computing." Dongarra will attend ACM's annual awards banquet in San Francisco on June 11, 2022, where he will be announced as the recipient of the ACM Turing Award.
For more than four decades, Dongarra has been a key participant or presidential researcher in several libraries, including LINPACK, BLAS, LAPACK, ScaLAPACK, PLASMA, MAGMA, and SLATE. Such libraries are written for single CPUs, parallel processing computers, multi-core connection points and several GPUs per node. From laptops to the world's faster very computers, his software libraries are widely used to implement high-performance scientific and engineering project calculations on such devices.
This library exhibits a number of in-depth technical innovations, for example: auto-tuning: in accordance with his new ATLAS project, which received a time-detection award at the 2016 worldwide very computing exchange, it seems that Dongarra has opened up the way to fully automate the way in which to find optimization of algorithmic main parameters, resulting in line-generation cores close to the best working efficiency, which is usually superior to the coding that is brought by way of the distributor.
Mixed Precision Arithmetic: In a 2006 worldwide very Computing Conference paper, Dongarra first utilized the diverse precision of floating-point arithmetic to quickly give precise solutions. As recently demonstrated in the HPL-AI benchmarks, this work has led to critical efficiencies in the use of artificial neural networks and unprecedented performance levels in the world's top-ranking extraordinary computers.
High-volume computing: Dongarra has opened up the case for partitioning medium- to large-sized aggregated diversion matrix computations (often used for simulation, modeling, and statistical analysis of data) into several-task computations, where chunks of daily tasks can be computed individually and with high concurrency. According to his thesis, "Performance,design,andautotuningofbatchedGEMMforGPUs," published in 2016, Dongarra led a cadre of developers in developing the BLAS specification of batch commands for this type of computation, and they also occur in the software libraries MAGMA and SLATE.
Dongarra has interacted internationally with many of these efforts, and has always been a driving force for innovation, maximizing performance and portability based on the continued development of technologies, while applying the most modern technologies to maintain reliable data results.
In addition, he led the development of the Message Passing Interface (MPI), the de facto standard for lifecycle messaging on parallel processing computing architectures, and its Performance API (PAPI), which ensures a socket that allows for the collection and generation of performance from heterogeneous operating system components. The specifications he has helped build, such as MPI, the LINPACK standard, and the Top500 very Computer Roster, underpin computational day-to-day tasks ranging from weather trends to climatic issues to dissecting data information from small-scale physics experiments.