Kerem Çamsari, assistant professor in the Department of Electrical and Computer Engineering at UC Santa Barbara, received a prestigious Young Investigator Award from the Office of Naval Research (ONR).
One of 32 junior faculty nationwide selected by ONR in 2022, Çamsari will receive a three-year, $510,000 grant to support his work designing a probabilistic computer to solve computational problems faster. and more efficiently.
“I feel humbled and honored to receive this award from the Office of Naval Research,” said Çamsari, who joined UCSB’s College of Engineering in 2020. “This is very generous funding that will support postdocs and graduate students, as well as the fabrication of the chips and the costs of the equipment we will need to carry out this research.
The rise of artificial intelligence (AI) and machine learning (ML) has created an IT crisis and a strong need for more energy-efficient and scalable hardware. A key step in AI and ML is making decisions based on incomplete data; the best approach is to generate a probability for each possible answer.
Current classical computers are not suitable for energy-efficient execution of these problems, thus intensifying the search for new computational approaches.
One solution scientists are looking for is quantum computers, which are powered by qubits. Unlike bits that power conventional computers and can exist in a 0 or 1 state, a qubit is a two-state system that can be in multiple states at once.
The phenomenon, known as superposition, allows quantum computers to perform computational functions exponentially faster than classical computers. However, qubits are extremely sensitive to their environment and must be maintained at very low temperatures, which requires significant amounts of energy.
Çamsari and his colleagues see a probabilistic computer as another solution that could solve difficult computational problems in AI and ML faster and more efficiently than classical and quantum computers.
In his ONR project, “Scalable Probabilistic Computers for Optimization and Quantum Simulation”, he aims to develop probabilistic computers based on nanodevices.
“In this project, we will investigate the limitations of probabilistic computers from a hardware, architectural, and algorithmic perspective,” said Çamsari, whose research on probabilistic computers dates back to his days at Purdue University. , where he completed his doctorate. and held a postdoctoral position.
“Ultimately, we want to solve computational problems faster, better, and more energy-efficiently,” he said.
Probabilistic computers are powered by probabilistic bits, or p-bits, which interact with other bits in the same system. Unlike classical computer bits, which are 0 or 1, and qubits in quantum computers, which exist in two states, p-bits fluctuate between positions. P-bits are non-overlapping and operate at room temperature.
Çamsari and his collaborators while at Purdue built a prototype that showed the potential of the device, solving the same optimization problems often targeted for quantum computers, while demonstrating a 10-fold reduction in energy and a 100x reduction in footprint required compared to a typical computer.
With seed funding from UCSB’s Institute for Energy Efficiency, Çamsari and Luke Theogarajan, vice president of UCSB’s ECE department, began in 2021 building a mid-size probabilistic computer that incorporates technology complementary metal oxide semiconductors (CMOS).
The ONR project will allow Çamsari to significantly expand this project to determine whether probabilistic computers can outperform all known classical methods in solving a set of practical problems, especially those that are naturally probabilistic.
“A fascinating scientific question is how much of the application space envisioned for quantum computers can be addressed by probabilistic computers,” he explained. “Their application to classical optimization and machine learning problems may be much more immediate than quantum computers, because probabilistic computers admit a much wider variety of practical implementations.”
Çamsari describes this project as “truly interdisciplinary” and says it requires both theoretical and experimental breakthroughs. The immediate goal is to solve difficult quantum optimization and simulation tasks by designing state-of-the-art probabilistic algorithms, modifying them according to the needs of the underlying hardware, and developing additional prototypes.
“The broader vision is to create domain-specific hardware that can connect unique characteristics of materials and devices to corresponding algorithms and applications. In the next era of computing, most of us would agree that it It’s one of the few ways to progress,” he said.
“Although this is a very difficult task, our group is uniquely qualified to meet it. We are extremely excited to begin this journey,” he said.
Developing probabilistic computers that solve computational problems faster and more efficiently than the best classical and near-term quantum computers could solve problems faced by the Department of Defense, such as supply chain logistics, traffic optimization, tactical communications and probabilistic decision making.
ONR, an agency of the executive branch of the Department of Defense, supports basic and applied research to increase fundamental knowledge, foster breakthroughs, and provide technology options for future naval capabilities and systems.
The office also provides technical advice to the Chief of Naval Operations and the Secretary of the Navy.
