Balkind: IGSB SW Impact Grant
CS Ass't. Prof. Jonathan Balkind among four potentially high-impact projects seeking to solve critical energy-efficiency challenges have been awarded more than $240,000 in cumulative funding related to UCSB's Institute for Energy Efficiency (IEE)
Excerpt from the COE News – "Investing in Social Impact"
IEE, the College of Engineering’s interdisciplinary research center, is dedicated to cutting-edge science and technologies that support an energy-efficient and sustainable future. Each project aligns with at least one of the institute’s key interdisciplinary thrusts: smart societal infrastructure, computing and communications, and the food-energy-water nexus.
Jonathan Balkind’s work received one of the two project awards from the Investment Group of Santa Barbara (IGSB) Software Impact grants, which support high-impact research of energy-efficient software that is likely to lead to commercialization and positively impact society. The selection committee also awarded $50,000 grants to two projects through the IEE Research Seed Grant Program. Seed grants are intended to help researchers produce preliminary results that can be used to apply for major external funding to expand their projects.
“Nurturing early-stage concepts with modest yet meaningful financial support not only jumpstarts scientific success but also cultivates and continues the culture of collaboration and discovery that thrives within the IEE and the university,” said IEE Director John Bowers, a distinguished professor of electrical and computer engineering, and materials.
“Whether they are being pursued by junior faculty or highly esteemed researchers, these four projects share key characteristics: they are strong and innovative proposals with significant potential to impact society,” added Mark Abel, the executive director of the IEE.
The four projects involve a total of five UCSB faculty members from the Departments of Chemical Engineering, Materials, Electrical and Computer Engineering, Computer Science, and Chemistry & Biochemistry.
Jonathan Balkind – "Empowering a Pie-in-the-Sky Idea"
Computer science assistant professor Jonathan Balkind wants to take a page out of the history books about the early days of graphics processing units (GPUs). Back then, researchers figured out how to shoehorn their data and code into low-level computer graphics, known as graphics kernels, in order to exploit the high-performance processing engines inside the GPUs. Once manufacturers understood the GPUs’ potential for high performance and energy efficiency, they generalized their designs, enabling radical improvements in computational energy efficiency for highly parallel workloads.
“The rise of GPUs serves as inspiration for my research group; only we want to make machine learning more efficient by moving data,” said Balkind, who previously received an Early CAREER Award from the National Science Foundation and a Trailblazer Fellowship from the Open Source Hardware Association.
Due to the widespread use of machine learning (ML), specialized processors designed to accelerate ML tasks, called tensor processing units (TPUs), are commonly found in modern computing systems. TPUs specialize in performing matrix multiplication, a fundamental operation in ML that combines the rows and columns of two matrices into a new matrix. Also referred to as accelerators, TPUs perform operations with high efficiency. The problem is that while an accelerator runs, the rest of the computing system, the central processing unit (CPU), remains active and simultaneously performs key functions, such as setting up and composing matrix multiplication kernels, as well as handling the computer’s input/output, and performing calculations and logic, all of which consumes large amounts energy.
“We want to perform more calculations on the TPU rather than relying so much on the CPU,” said Balkind. “TPUs are optimized specifically for machine learning, so there is a tremendous potential to reduce the amount of time and energy required to complete an operation if we are able to broaden the functionality of the accelerators.”
Initial work on a promising solution has already been completed by a master’s student and undergraduate students in Balkind’s research group. The team built a new software program, called the Mullifier, to translate existing high-level programming source code and generate an equivalent lower-level language, which included series of matrix multiplications for the accelerator. To date, their program has handled arithmetic, branching, looping, as well as complex operations like stack and memory management.
“This grant allows us to examine our hardware’s design in order to expand the amount of code that we could support,” explained Balkind. “The more code and pathways between different units that we can incorporate, the faster and more energy efficient the process will be.”
The opportunity to pursue, what he described as a “crazy idea” will allow his research group to investigate if small changes in hardware could have a big impact on energy efficiency.
“One of the reasons why I came to UCSB was because the scientific community encourages people to think outside the box,” he said. “This is a great example of the IEE and this campus empowering students and researchers to pursue pie-in-the-sky research that could potentially impact the world.”
