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karan sapra karan sapra research scientist nvidia ph d computer engineering ks sapra karan at gmail fall 2017 nvidia applied deep learning research deep learning for computer vision and realtime graphics fall 2014 oak ridge national lab internship continued hetrogenous framework development for exascale computing and hetrogenous architecture integration with cesm workflow summer 2014 oak ridge national lab internship hetrogenous framework development for exascale computing and hetrogenous architecture 2011 2018 clemson university computer engineering ph d student framework for life cycle enrichment of hpc applications towards exascale heterogeneous architecture advisor melissa c smith 2011 bachelor s degree major in computer engineering and minor in mathematical science fall 2009 summer 2010 spring 2010 summer 2011 adtran inc co op internsip worked on creating new features debugging features in adtran operating system for network hardware equipment 2008 enrolled in computer engineering at clemson university i am a research scientist at nvidia in santa clara working computer vision and real time computer graphics i completed my phd student from clemson university working with melissa c smith i received a b sc in computer engineering with mathematical science minor from clemson university in 2011 background i have worked on p2p cloud networking and network security and sensors during my undergraduate first and second year of my ph d i also worked at adtran inc for 1 5 year as a software engineer during my phd i have worked on multiple projects mapping and performance prediction on high performance architecture global gene alignment in collaboration with dr alex f feltus enabling remote surgery using hpc and secure computing using gpus in collaboration with dr richard brooks i also collabrated with and worked at ornl on functional partitioning framework for enabling a2a framework and node local post processing current projects i work in the applied research deep learnign team at nvidia applying dl for graphics my complete cv is available here publications partial convolution based padding g liu k shih t wang f reda k sapra z yu a tao b catanzaro https arxiv org abs 1811 11718 improving semantic segmentation via video propagation and label relaxation y zhu k sapra f reda k shih s newsam a tao b catanzaro accepted talk cvpr 2019 g3na v gpu enabled tool for mining and aligning complex gene interaction graphs k sapra f feltus m smith and j levine accepted talk gpu technology conference gtc 2016 san jose california framework for lifecycle enrichment of hpc applications on exascale heterogeneous architecture k sapra ph d doctoral showcase supercomputing sc 2015 texas austin hpc enabled real time remote processing of laparoscopic surgery k sapra z ronaghi r izard e duffy m c smith kc wang d kwartowitz accepted poster supercomputing sc 2015 texas austin enhancing collusion resilience in reputation systems h shen y lin k sapra z li ieee transactions on parallel and distributed systems tpds 2015 g3na gpu enabled gene network alignment tool k sapra f feltus m smith gpu technology conference gtc 2015 san jose california rial resource intensity aware load balancing in clouds l chen h shen k sapra international conference on computer communication infocom 2014 a social network integrated reputation system for cooperative p2p file sharing k chen h shen k sapra g liu international conference on communications and network icccn 2013 nassau circumventing keyloggers and screendump k sapra b husain r brooks m smith malware 2013 puerto rico taxonomy cube a multi dimension application to architecture mapping k sapra early dissertation showcase supercomputing conference colorado 2013 collusion detection in reputation systems for peer to peer networks k sapra h shen z li ieee transaction on parallel and distributed systems tpds submitted cedar an optimal and distributed strategy for packet recovery in wireless network c qui h shen s soltani k sapra h jiang j hallstorm ieee international conference on computer communication infocomm april 2013 leveraging social networks to combat collusion in reputation systems for peer to peer networks z li h shen k sapra ieee journal on transaction of computers tc cooperative end to end traffic redundancy elimination for reducing cloud bandwidth cost l yu k sapra h shen lin ye ieee international conference on network protocols icnp oct 2012 collusion detection in reputation systems for peer to peer networks z li h shen k sapra the 41st international conference on parallel processing icpp sept 2012 leveraging social networks to combat collusion in reputation systems for peer to peer networks z li h shen k sapra ieee international parallel and distributed processing symposium ipdps may 2011 anchorage alaska fast image mosaicking using optical flow k sapra s birchfield proc of ieee southeastcon secon 2011 some of my previous projects improving semantic segmentation via video propagation and label relaxation we propose an effective video prediction based data synthesis method to scale up training sets in order to improve the accuracy of semantic segmentation networks we also introduce a joint propagation strategy to alleviate mis alignments in synthesized samples furthermore we present a novel boundary relaxation technique to mitigate label noise the label relaxation strategy can also be used for human annotated labels and not just synthesized labels we achieve state of the art performance on three benchmark datasets cityscapes camvid and kitti a summarization video demo can be watched below yi zhu co author karan sapra co author fitsum a reda kevin j shih shawn newsam andrew tao and bryan catanzaro partial conv based padding we present a simple yet effective padding scheme that can be used as a drop in module for existing convolutional neural networks we call it partial convolution based padding with the intuition that the padded region can be treated as holes and the original input as non holes specifically during the convolution operation the convolution results are re weighted near image borders based on the ratios between the padded area and the convolution sliding window area extensive experiments with various deep network models on imagenet classification and semantic segmentation demonstrate that the proposed padding scheme consistently outperforms standard zero padding with better accuracy guilin liu kevin j shih ting chun wang fitsum a reda karan sapra zhiding yu andrew tao bryan catanzaro application to architecture a2a mapping one of the challenging task is mapping finding an optimal architecture for a given application optimality can be either performance scaling energy watt my dissertation will focus on finding an optimal architecture for a given application karan sapra melissa c smith heterogeneous functional partitioning framework one of the challenging task in computing facilities such as titan supercomputer is under or non utilization of cores or and the accelerator on a node we propose framework that allows offloading of i o statistics and other in program functionality to be offloaded to the cores and accelerator to decrease the run time and increase the utilization of cores on a node and the overall computing facilities karan sapra saurabh gupta ornl atcheley scott ornl ross miller ornl sudarshan vazhkudai ornl melissa c smith global gpgpu based gene net alignment and visualization g3na we utilize gpgpus for aligning and visualizing large scale gene interaction networks we can perform multiple alignment between biological networks within less minute our maize rice network alignment takes 35 seconds on nvidia k40 each network is 2000 nodes and 40000 edges we currently are extending this xeon phis fpga and multi core architecture website video interview with nvidia at sc15 november 2015 austin tx karan sapra melissa c smith alex f feltus hpc enabled real time remote processing of laparoscopic surgery laparoscopic surgery is a minimally invasive surgical technique where surgeons insert a small video camera into the patient s body to visualize internal organs and use small tools to perform surgical procedures however the benefit of small incisions has a drawback of limited subsurface tissue visualization image guided surgery igs uses images to map subsurface structures and can reduce the limitations of laparoscopic surgery one particular laparoscopic camera system is the vision system of the davinci robotic surgical system processing this huge stream of data on a single or dual node setup is a challenging task thus we propose high performance computing hpc enabled framework for laparoscopic surgery which is secure reliable and scalable karan sapra zahra ronaghi ryan izard edward duffy melissa c smith kuang ching wang david m kwartowitz show more domain name generation algorithm we implement two domain name generation algorithms using probabilistic context free grammar pcfg and hidden markov model hmm to evade detection routines we compare our dgas with three popular detection routine kullback leibler kl distance jaccard index ji and edit distance ed detection techniques karan sapra benafsh husain fu yu richard r brooks keyloggers and screendumps keyloggers hardware or software and screendumps of virtual keyboards by the local machine to counter these attacks we use directx 9 libraries 3 on windows or linux 5 operating systems our approach uses a remote server that communicates securely with the local process the direct x mode that we use executes in the gpu while being directly displayed on the screen there is no direct communication between the operating system and the gpu storage which allows us to communicate with the user securely even if the local machine is compromised we present a simple prototype application of this approach which supports web browsing karan sapra benafsh husain richard r brooks melissa smith cloud load balancing robust infrastructure as a service iaas clouds currently perform load balancing by migrating virtual machines vms from heavily loaded physical machines pms to lightly loaded pms the unique features of clouds pose formidable challenges to achieving effective and efficient load balancing we propose a resource intensity aware load balancing method rial for each pm rial dynamically assigns different weights to different resources according to their usage intensity in the pm which significantly reduces the time and cost to achieve load balance and avoids future load imbalances we extensively trace driven simulation results and real world experimental results show the superior performance of rial compared to other load balancing methods helen shen karan sapra cooperative end to end traffic redundancy elimination for reducing cloud bandwidth cost pay as you go service model impels cloud customers to reduce the usage cost of bandwidth traffic redundancy elimination tre has been shown to be an effective solution for reducing bandwidth costs and has recently captured significant attention in the cloud environment we propose a sender and receiver cooperative end to end tre solution core for efficiently identifying and removing both short term and long term redundancy through a two layer redundancy detection design and one single pass algorithm for chunking and fingerprinting core efficiently carries out cooperative operations between the sender and the receiver by extensive evaluation with several real traces we show that core is able to identify both short term and long term redundancy with low additional cost while ensuring tre efficiency from data changes lei yu karan sapra helen shen p2p collusion detection and avoidance peer to peer networks p2ps many autonomous nodes without preexisting trust relationships share resources e g files between each other due to their open environment p2ps usually employ reputation systems to provide guidance in selecting trustworthy resource providers for high system reliability and security a reputation system computes and publishes reputation score for each node based on a collection of opinions from others about the node we analyze transaction ratings in the amazon and overstock online transaction platforms during one year the analysis of real trace confirms the existence of collusion as well as its important behavior characteristics and influence on reputation values in real reputation systems we also proposed a collusion detection method to specifically thwart collusion behaviors we further optimized the method by reducing the computing cost karan sapra helen shen fast image mosaicking using optical flow method of mosaicking a series of unidirectional 2 d motional images independent of type of motion in single plane i e planar or circular in nature assuming a unidirectional displacement is occurring with each frame the resultant image after mosaicking can be a color image even though major computation is done on gray scale images and thus making the mosaicking faster and output more aesthetic karan sapra stan birchfield 20 pageviews apr 27th may 27th