Algorithm Engineering in Robust Optimization

Robust optimization is a young and emerging field of research having received a considerable increase of interest over the last decade. In this paper, we argue that the the algorithm engineering methodology fits very well to the field of robust optimization and yields a rewarding new perspective on both the current state of research and open research directions. To this end we go through the algorithm engineering cycle of design and analysis of concepts, development and implementation of algorithms, and theoretical and experimental evaluation. We show that many ideas of algorithm engineering have already been applied in publications on robust optimization. Most work on robust optimization is devoted to analysis of the concepts and the development of algorithms, some papers deal with the evaluation of a particular concept in case studies, and work on comparison of concepts just starts. What is still a drawback in many papers on robustness is the missing link to include the results of the experiments again in the design

Supraselective intra-arterial chemotherapy: evaluation of treatment-related complications in advanced retinoblastoma

Lejla Mutapcic Vajzovic1, Timothy G Murray1, Mohammad A Aziz-Sultan2, Amy C Schefler1, Stacey Quintero Wolfe2, Ditte Hess1, Cristina E Fernandes3, Sander R Dubovy1,41Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, FL, USA; 2Department of Neurological Surgery, University of Miami/Jackson Memorial Hospital, Miami, FL, USA; 3Department of Pediatrics, University of Miami Miller School of Medicine, Miami, FL, USA; 4Florida Lions Oculopathology Laboratory, Miami, FL, USA Purpose: The purpose of this study is to report the complication profile and safety evaluation of supraselective intra-arterial melphalan chemotherapy in children undergoing treatment with advanced retinoblastoma.Methods: Twelve eyes of 10 children with advanced retinoblastoma (Reese-Ellsworth Group Vb or International Classification Group D) were treated with supraselective intra-ophthalmic artery infusion of melphalan. Eleven eyes of nine children had previously failed traditional management with systemic chemotherapy and laser ablation and underwent intra-ophthalmic artery infusion of melphalan as an alternative to enucleation. Serial ophthalmic examinations, retinal photography, and ultrasonographic imaging were used to evaluate treatment regime.Results: Ophthalmic artery cannulation was successfully performed in 12 eyes of 10 patients (total 16 times). Striking regression of tumor, subretinal and vitreous seeds were seen early in each case. No severe systemic side effects occurred. Grade III neutropenia was seen in one patient. No transfusions were required. Three patients developed a vitreous hemorrhage obscuring tumor visualization. One patient developed periocular edema associated with inferior rectus muscle inflammation per orbital MRI. This same patient had scattered intraretinal hemorrhages and peripapillary cotton wool spots consistent with a Purtscher’s-like retinopathy that resolved spontaneously. At the 6-month follow-up examination, nine eyes had no evidence of tumor progression, whereas three eyes were enucleated for tumor progression. In each enucleated case, viable tumor was identified on histopathologic examination.Conclusions: Ophthalmic intra-arterial infusion with melphalan is an excellent globe-conserving treatment option in advanced retinoblastoma cases with minimal systemic side effects. Local toxicities include microemboli to the retina and choroid (1/12, 8%), vitreous hemorrhage (3/12, 25%), and myositis (1/12, 8%). Enucleation remained a definitive treatment for tumor progression in 3 of 12 eyes in this small case series with limited follow-up. Further studies are necessary to establish the role of supraselective intra-arterial melphalan chemotherapy for children with retinoblastoma.Keywords: retinoblastoma, intra-arterial chemotherapy, melphala

Temperature Control of High-Performance Multi-core Platforms Using Convex Optimization

With technology advances, the number of cores integrated on a chip and their speed of operation is increasing. This, in turn is leading to a significant increase in chip temperature. Temperature gradients and hot-spots not only affect the performance of the system, but also lead to unreliable circuit operation and affect the life-time of the chip. Meeting the temperature constraints and reducing the hot-spots are critical for achieving reliable and efficient operation of complex multi-core systems. In this work, we present Pro-Temp, a convex optimization based method that pro-actively controls the temperature of the cores, while minimizing the power consumption and satisfying application performance constraints. The method guarantees that the temperature of the cores are below a user-defined threshold at all instances of operation, while also reducing the hot-spots. We perform experiments on several realistic multi-core benchmarks, which show that the proposed method guarantees that the cores never exceed the maximum temperature limit, while matching the application performance requirements. We compare this to traditional methods, where we find several temperature violations during the operation of the system

Temperature control of high-performance multi-core platforms using convex optimization

With technology advances, the number of cores integrated on a chip and their speed of operation is increasing. This, in turn is leading to a significant increase in chip temperature. Temperature gradients and hot-spots not only affect the performance of the system, but also lead to unreliable circuit operation and affect the life-time of the chip. Meeting the temperature constraints and reducing the hot-spots are critical for achieving reliable and efficient operation of complex multi-core systems. In this work, we present Pro-Temp, a convex optimization based method that pro-actively controls the temperature of the cores, while minimizing the power consumption and satisfying application performance constraints. The method guarantees that the temperature of the cores are below a user-defined threshold at all instances of operation, while also reducing the hot-spots. We perform experiments on several realistic multi-core benchmarks, which show that the proposed method guarantees that the cores never exceed the maximum temperature limit, while matching the application performance requirements. We compare this to traditional methods, where we find several temperature violations during the operation of the system