Embedded and Reconfigurable Research
Reconfigurable Embedded Systems for Medical Applications
Constant Computation of Wireless Sensor Networks 2008-PRESENT
F.
Dabiri, A. Vahdatpour, H. Noshadi, M. Sarrafzadeh
A
new model of computation for distributed systems, called constant
computation constructs
the best possible
solution for the problem while using a bounded amount of computation,
communication, and memory.
Lightweight sensor networks usually form a topology after deployment and do not
possess a pre-defined structure.
Therefore, global information about the network is either costly or impossible.
Current distributed algorithms share a fair amount of global information.
However, in these algorithms, the computation is asymptotically in the order of
f(n), where f(n) is non-constant function of n. In our constant model of
computation, each
lightweight embedded system is such that, memory usage, communication iterations
and data processing are in O(1).
WESTS (Wireless Embedded medical SysTems) 2006-PRESENT
T.
Massey, F. Dabiri, H. Noshadi, G. Marfia, A. Chang, J. Chen, S. Jung, R. Tan, C. Lin, D.
Jea, J. Schmidt, M. Gerla, M. Sarrafzadeh
Advancements in nanotechnology make it possible to fabricate a Body Sensor Network (BSN) with miniature embedded sensors that monitor physiological activities occurring inside of the body and simultaneously probe the outside environment for harmful chemicals, dangerous radiation levels, and a more general score of other hostile events. Wireless Embedded medical SysTemS (WESTS) will allow for the efficient monitoring of physiological occurrences in the body. HealthNet will allow the communications of WESTS with the infrastructure for remote monitoring.
CustoMed (Customizable Medical Monitoring Device) 2004-PRESENT
F. Dabiri, T. Massey, A. Nahapatian, H. Noshandi, S. Chaudhry, R.
Jafari, M. Sarrafzadeh
CustoMed is a new architecture that will reduce the customization and reconfiguration time for systems that use reconfigurable embedded systems through "Med Nodes", stand-alone components consisting of a processing unit, a battery and various sensors for physiological reading from the human body. Research challenges in the area of reconfiguration, security, power awareness, communication, software partitioning, fault tolerance, and adaptability are explored.
RFAB (Reconfigurable Fabric) 2002-2005
R.
Jafari, F. Dabiri, F. Chen, V. Raghunathan, T. Schoellhammer, D. Sievers, B. Wu,
D. Estrin, G. Reinman, M. Sarrafzadeh, M. Srivastava, Y. Yang
RFab consists of a medical vest for sensor-driven personalized transdermal drug-delivery for medical treatment. RFab research explores environmental dynamics, physical coupling, resource constraints, infrastructure support, and robustness requirements in this wearable application.
GPGPU
General-Purpose Computation on Graphics Processing Units: Higher Performance Computing
2007-PRESENTWith the introduction of inexpensive, single-chip, massively parallel platforms such as the new generation of GPU architectures, more developers will be creating real-life applications for these platforms. However, traditional programming models are not entirely suitable for development on such many-core architectures and unreasonable loss of performance can arise from direct porting of applications to them in spite of significant computational power of these platforms. We are currently studying and developing structured transformation methods that could remove existing bottlenecks in applications to make them more suitable for high performance many-core architectures. We are focusing on medical imaging and video processing applications as case studies. In addition, through collaboration with the UCLA Department of Radiology, novel high-performance medical imaging algorithms are being designed and studied for these platforms.
VLSI
Z. Karimi, T. Taghavi, B. Choi, X. Yang, M. Wang, M. Sarrafzadeh
Dragon is a fast, effective standard cell placement tool for both variable-die and fixed-die ASIC design. Dragon enables wirelength and routable optimization by combining power hypergraph partitioning package (hMetis) with simulated annealing techniques.