Our lab primarily focuses on energy-efficient computer architectures and emerging computing computing paradigms (including but not limited to neuromorphic computing). Our research broadly covers computing systems (including software/hardware interactions) and how emerging technologies, programming languages, and applications shape the future generation computing systems, particularly from the energy efficiency and reliability point of views.

Motivated by the fact that Moore’s Law — the most prominent phenomenon for a computer architect — is under pressure, our lab’s research agenda has directions towards both software and hardware solutions for  computationally demanding applications, such as machine learning, big-data analytics, general artificial intelligence, and scientific applications. To maintain the ever-increasing computing demand of such contemporary applications, we have to survive either by scaling up the systems (building highly parallel and distributed systems), or by specializing on important set of algorithms/operations (e.g., matrix-vector multiplication), until disruptive post-CMOS technologies operating at orders of magnitude efficiency margins become feasible to manufacture and commercially viable.  Consequently, our research focus can be split into two general directions: (i) addressing the computational challenges of today, and (ii) exploring the opportunities for the future (considering both SW and HW).

We can broadly list our research efforts under the following topics:

  • Hardware and Software Techniques for Energy-Efficient Computing (including approximation, code optimization, parallelization, microarchitectural enhancements)
  • Architecture and Programming Models for Emerging Computing Paradigms (Neuromorphic Computing, Spiking Neural Networks)
  • Parallel Programming, Programming for Heterogeneous Systems (including CPUs, GPUs, FPGAs, and accelerators)
  • Sustainable Computing

Information for Prospective Students:

We have openings for Ph.D. students to work on Tübitak 2232 Project in the area of Heterogeneous Computing. If you are interested in programming on CPUs, GPUs, FPGAs, accelerators and developing runtime systems, please contact Dr. Akturk.

We have openings for Ph.D. and M.S. students to work on KDT-JU Project in the area of Green Electronics. If you are interested in any of the topics that include life-cycle-assessment of computing devices, the environmental impact of electronics,  sustainable computing and ways to reduce e-waste, please contact Dr. Akturk.

We have openings for Ph.D. and M.S. students to work on Tübitak 1001 Project in the area of Neuromorphic Computing. If you are interested in finding ways to build more efficient learning algorithms and implementing them on biologically inspired neuromorphic systems, please contact Dr. Akturk.

If you are an undergraduate student and want to get involved with research activities in our lab, please contact Dr. Akturk.