All posts by Mosharaf

Carbyne Accepted to Appear at OSDI’2016

Update: Camera-ready version is available here now!

With the wide adoption of distributed data-parallel applications, large-scale resource scheduling has become a constant source of innovation in recent years. There are tens of scheduling solutions that try to optimize for objectives such as user-level fairness, application-level performance, and cluster-level efficiency. However, given the well-known tradeoffs between fairness, performance, and efficiency, these solutions have traditionally focused … Continue Reading ››

EC-Cache Accepted to Appear at OSDI’2016

Update: Camera-ready version is available here now!

In-memory caching is the de facto solution to enable low latency analytics over large datasets. While caching objects,  one must be careful about maximizing the number of requests that can be served from memory in the presence of popularity skew, background load imbalance, and server failures. Traditional solutions use selective replication, i.e., … Continue Reading ››

Received SIGCOMM Doctoral Dissertation Award

About a week or so ago Bruce Maggs, SIGCOMM's awards chair, kindly informed me over the phone that my dissertation on coflows has been selected for the 2015 ACM SIGCOMM Doctoral Dissertation Award. The committee for the award included Ratul Mahajan, Dina Papagiannaki, Laurent Vanbever (chair), and Minlan Yu, and the citation reads:
Chowdhury's … Continue Reading ››

CODA Accepted to Appear at SIGCOMM’2016

Update: Camera-ready version is available here now!

Since introducing the coflow abstraction in 2012, we've been working hard to make it practical one step at a time. Over the years, we've worked on efficient coflow scheduling, removed clairvoyance requirements in coflow scheduling, and performed fair sharing among coexisting coflows. Throughout all these efforts, one requirement remained constant: all … Continue Reading ››

HUG Accepted to Appear at NSDI’2016

Update: Camera-ready version is available here now!

With the advent of cloud computing and datacenter-scale applications, simultaneously dealing with multiple resources is the new norm. When multiple parties have multi-resource demands, fairly dividing these resources  (for some notion of fairness) is a core challenge in the resource allocation literature. Dominant Resource Fairness (DRF) in NSDI'2011 was the first work to … Continue Reading ››

I Have Multiple Openings for Graduate Students!

If you are already a student in Michigan, drop me an email.

My work focuses on increasing application-infrastructure symbiosis in datacenter-scale, rack-scale, and geo-distributed computing, both to improve today's data-intensive applications and to enable new data-driven applications on next-generation hardware. I'm looking for graduate students who are interested in systems, networking, and data-intensive computing, and are not afraid … Continue Reading ››