Hi. I'm Justin, a software engineer working out of Boston.
I think distributed systems, datacenter networks, and peer-to-peer networks are pretty neat.
A few things I've recently had the pleasure of working on:
- Understanding and building systems for emerging datacenter networks and architectures. For example, my work on resource disaggregation and bandwidth allocation in Google's inter-datacenter WAN, BwE.
- Building tools to better understand behavior in blockchain architectures. For example, my work with BloXroute to build a blockchain measurement infrastructure that concurrently tracks data movement across thousands of peers.
- Tackling the network latency bottleneck when moving high performance computing applications to the cloud. For example, my work with the UIUC Parallel Programming Lab and Charmworks on reducing latency through duplicating work.
I also rock climb, play the guitar, and mess around with blockchains - right now I'm building out a music community site
Built a blockchain measurement infrastructure from the ground up to measure data propagation through the underlying peer-to-peer network. This required concurrently processing tens of thousands of messages from thousands of peers every second. Designed and facilitated experiments to highlight BloXroute performance benefits and identify areas of improvement for the dev team.
Researched distributed data processing systems for an emerging datacenter architecture, resource disaggregation, that tolerate higher network latency while leveraging fine-grained resource multiplexing and application elasticity provided by disaggregation. Seperate work involved characterizing information leakage in cloud distributed systems and building a new privacy-aware key-value store that guarentees information leakage is not abusable.
Worked with the Network Infrastructure team in Sunnyvale, CA to to improve network bandwidth allocation on Google's inter-datacenter WAN. This work builds upon Google's hierarchal bandwidth allocator, BwE. It involved developing new bandwidth allocation techniques that leveraged machine learning and real-time control literature; and algorithmic analysis of existing bandwidth allocation techniques.
Worked with the Azure Data Warehouse team in Aliso Viejo, CA to build a prototype for a distributed query store for Azure SQL Data Warehouse. This enabled more extensive query monitoring and debugging for distributed queries, especially in the case of complex query execution plans spanning many servers.
Researched techniques for realizing latency-sensitive high performance computing applications in less predictable and higher latency environments, such as commercial clouds. This involved optimizing application communication and minimizing latency introduced by the runtime system through lock-free algorithms. Other work included designing a RDMA-backed message passing interface for CRAY machines, and building parallel object replication techniques for load balancing.
Worked to optimize a parallel program runtime system Charm++, a parallel object-oriented programming language, for performance. Additionally, modified parallel algorithms for shared memory parallel applications to operate scalably in a distributed memory context.