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 * ACM AM Turing Award 2021


ACM TURING AWARD HONORS JACK J. DONGARRA FOR PIONEERING CONCEPTS AND METHODS
WHICH HAVE RESULTED IN WORLD-CHANGING COMPUTATIONS


DONGARRA'S ALGORITHMS AND SOFTWARE FUELED THE GROWTH OF HIGH-PERFORMANCE
COMPUTING AND HAD SIGNIFICANT IMPACTS IN MANY AREAS OF COMPUTATIONAL SCIENCE
FROM AI TO COMPUTER GRAPHICS

New York, NY, March 30, 2022 – ACM, the Association for Computing Machinery,
today named Jack J. Dongarra recipient of the 2021 ACM A.M. Turing Award for
pioneering contributions to numerical algorithms and libraries that enabled high
performance computational software to keep pace with exponential hardware
improvements for over four decades. Dongarra is a University Distinguished
Professor of Computer Science in the Electrical Engineering and Computer Science
Department at the University of Tennessee. He also holds appointments with Oak
Ridge National Laboratory and the University of Manchester.

The ACM A.M. Turing Award, often referred to as the “Nobel Prize of Computing,”
carries a $1 million prize, with financial support provided by Google, Inc. It
is named for Alan M. Turing, the British mathematician who articulated the
mathematical foundation and limits of computing.

Dongarra has led the world of high-performance computing through his
contributions to efficient numerical algorithms for linear algebra operations,
parallel computing programming mechanisms, and performance evaluation tools. For
nearly forty years, Moore’s Law produced exponential growth in hardware
performance. During that same time, while most software failed to keep pace with
these hardware advances, high performance numerical software did—in large part
due to Dongarra’s algorithms, optimization techniques, and production-quality
software implementations.

These contributions laid a framework from which scientists and engineers made
important discoveries and game-changing innovations in areas including big data
analytics, healthcare, renewable energy, weather prediction, genomics, and
economics, to name a few. Dongarra’s work also helped facilitate leapfrog
advances in computer architecture and supported revolutions in computer graphics
and deep learning.

Dongarra’s major contribution was in creating open-source software libraries and
standards which employ linear algebra as an intermediate language that can be
used by a wide variety of applications. These libraries have been written for
single processors, parallel computers, multicore nodes, and multiple GPUs per
node. Dongarra’s libraries also introduced many important innovations including
autotuning, mixed precision arithmetic, and batch computations.

As a leading ambassador of high-performance computing, Dongarra led the field in
persuading hardware vendors to optimize these methods, and software developers
to target his open-source libraries in their work. Ultimately, these efforts
resulted in linear algebra-based software libraries achieving nearly universal
adoption for high performance scientific and engineering computation on machines
ranging from laptops to the world’s fastest supercomputers. These libraries were
essential in the growth of the field—allowing progressively more powerful
computers to solve computationally challenging problems.

“Today’s fastest supercomputers draw headlines in the media and excite public
interest by performing mind-boggling feats of a quadrillion calculations in a
second,” explains ACM President Gabriele Kotsis. “But beyond the understandable
interest in new records being broken, high performance computing has been a
major instrument of scientific discovery. HPC innovations have also spilled over
into many different areas of computing and moved our entire field forward. Jack
Dongarra played a central part in directing the successful trajectory of this
field. His trailblazing work stretches back to 1979, and he remains one of the
foremost and actively engaged leaders in the HPC community. His career certainly
exemplifies the Turing Award’s recognition of ‘major contributions of lasting
importance.’”

“Jack Dongarra's work has fundamentally changed and advanced scientific
computing,” said Jeff Dean, Google Senior Fellow and SVP of Google Research and
Google Health. “His deep and important work at the core of the world's most
heavily used numerical libraries underlie every area of scientific computing,
helping advance everything from drug discovery to weather forecasting, aerospace
engineering and dozens more fields, and his deep focus on characterizing the
performance of a wide range of computers has led to major advances in computer
architectures that are well suited for numeric computations.”

Dongarra will be formally presented with the ACM A.M. Turing Award at the annual
ACM Awards Banquet, which will be held this year on Saturday, June 11 at the
Palace Hotel in San Francisco.

SELECT TECHNICAL CONTRIBUTIONS

For over four decades, Dongarra has been the primary implementor or principal
investigator for many libraries such as LINPACK, BLAS, LAPACK, ScaLAPACK,
PLASMA, MAGMA, and SLATE. These libraries have been written for single
processors, parallel computers, multicore nodes, and multiple GPUs per node. His
software libraries are used, practically universally, for high performance
scientific and engineering computation on machines ranging from laptops to the
world’s fastest supercomputers.

These libraries embody many deep technical innovations such as:

Autotuning: through his 2016 Supercomputing Conference Test of Time
award-winning ATLAS project, Dongarra pioneered methods for automatically
finding algorithmic parameters that produce linear algebra kernels of
near-optimal efficiency, often outperforming vendor-supplied codes.

Mixed precision arithmetic: In his 2006 Supercomputing Conference paper,
“Exploiting the Performance of 32 bit Floating Point Arithmetic in Obtaining 64
bit Accuracy,” Dongarra pioneered harnessing multiple precisions of
floating-point arithmetic to deliver accurate solutions more quickly. This work
has become instrumental in machine learning applications, as showcased recently
in the HPL-AI benchmark, which achieved unprecedented levels of performance on
the world’s top supercomputers.

Batch computations: Dongarra pioneered the paradigm of dividing computations of
large dense matrices, which are commonly used in simulations, modeling, and data
analysis, into many computations of smaller tasks over blocks that can be
calculated independently and concurrently. Based on his 2016 paper,
“Performance, design, and autotuning of batched GEMM for GPUs,” Dongarra led the
development of the Batched BLAS Standard for such computations, and they also
appear in the software libraries MAGMA and SLATE.

Dongarra has collaborated internationally with many people on the efforts above,
always in the role of the driving force for innovation by continually developing
new techniques to maximize performance and portability while maintaining
numerically reliable results using state of the art techniques. Other examples
of his leadership include the Message Passing Interface (MPI) the de-facto
standard for portable message-passing on parallel computing architectures, and
the Performance API (PAPI), which provides an interface that allows collection
and synthesis of performance from components of a heterogeneous system. The
standards he helped create, such as MPI, the LINPACK Benchmark, and the Top500
list of supercomputers, underpin computational tasks ranging from weather
prediction to climate change to analyzing data from large scale physics
experiments.

Biographical Background

Jack J. Dongarra has been a University Distinguished Professor at the University
of Tennessee and a Distinguished Research Staff Member at the Oak Ridge National
Laboratory since 1989. He has also served as a Turing Fellow at the University
of Manchester (UK) since 2007. Dongarra earned a B.S. in Mathematics from
Chicago State University, an M.S. in Computer Science from the Illinois
Institute of Technology, and a Ph.D. in Applied Mathematics from the University
of New Mexico.

Dongarra’s honors include the IEEE Computer Pioneer Award, the SIAM/ACM Prize in
Computational Science and Engineering, and the ACM/IEEE Ken Kennedy Award. He is
a Fellow of ACM, the Institute of Electrical and Electronics Engineers (IEEE),
the Society of Industrial and Applied Mathematics (SIAM), the American
Association for the Advancement of Science (AAAS), the International
Supercomputing Conference (ISC), and the International Engineering and
Technology Institute (IETI). He is a member of the National Academy of
Engineering and a foreign member of the British Royal Society.


ABOUT THE ACM A.M. TURING AWARD

The A.M. Turing Award was named for Alan M. Turing, the British mathematician
who articulated the mathematical foundation and limits of computing, and who was
a key contributor to the Allied cryptanalysis of the Enigma cipher during World
War II. Since its inception in 1966, the Turing Award has honored the computer
scientists and engineers who created the systems and underlying theoretical
foundations that have propelled the information technology industry.


ABOUT ACM

ACM, the Association for Computing Machinery, is the world's largest educational
and scientific computing society, uniting educators, researchers and
professionals to inspire dialogue, share resources and address the field's
challenges. ACM strengthens the computing profession's collective voice through
strong leadership, promotion of the highest standards, and recognition of
technical excellence. ACM supports the professional growth of its members by
providing opportunities for life-long learning, career development, and
professional networking.

Contact:
Jim Ormond
212-626-0505
ormond@hq.acm.org

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