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An overview of the SatNOGS project, a network of satellite ground stations around the world, optimized for modularity, built from readily available and affordable tools and resources. The rate of Low Earth Orbit (LEO) satellite launches increases with the participation of old and new entities. In this growing environment, SatNOGS provides a scalable and modular solution to track, identify, receive telemetry from, monitor, and assist operators in command/control of satellites. The SatNOGS global community, dedicated to its free and open-source values, develops hardware ground station designs (antennas, rotators, electronics), software for SDR-based communications, satellite scheduling and mission monitoring platforms. SatNOGS continuously develops and improves its infrastructure to allow observers to use this networked ground segment and remotely operate SatNOGS ground stations around the world. It also provides an easy way to store, access and view increasingly received satellites data, by supporting VHF, UHF, L and S bands.

This poster has been presented in the 4th Summit on Gender Equality in Computing, 2022. It studies the problem of efficiently constructing data series indexes on multi-node environments, while still exploiting the computation power of the multiple cores supported on each node.

The availability of Non-Volatile Main Memory (known as NVMM) enables the design of recoverable concurrent algorithms. We study the power of software combining in achieving recoverable synchronization and designing persistent data structures. Software combining is a general synchronization approach, which attempts to simulate the ideal world when executing synchronization requests (i.e., requests that must be executed in mutual exclusion). A single thread, called the combiner, executes all active requests, while the rest of the threads are waiting for the combiner to notify them that their requests have been applied. Software combining significantly decreases the synchronization cost and outperforms many other synchronization techniques in various cases. We identify three persistence principles, crucial for performance, that an algorithm's designer has to take into consideration when designing highly-efficient recoverable synchronization protocols or data structures. We illustrate how to make the appropriate design decisions in all stages of devising recoverable combining protocols to respect these principles. Specifically, we present two recoverable software combining protocols, satisfying different progress properties, that are many times faster and have much lower persistence cost than a large collection of existing persistent techniques for achieving scalable synchronization. We build fundamental recoverable data structures, such as stacks and queues, based on these protocols that outperform by far existing recoverable implementations of such data structures. We also provide the first recoverable implementation of a concurrent heap and present experiments to show that it has good performance when the size of the heap is not very large., This paper has received a best paper award in the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (2022).

We study the performance power of software combining in designing recoverable algorithms and data structures. We present two recoverable synchronization protocols, one blocking and another wait-free, which illustrate how to use software combining to achieve both low persistence and synchronization cost. Our experiments show that these protocols outperform by far state-of-the-art recoverable universal constructions and transactional memory systems. We built recoverable queues and stacks, based on these protocols, that exhibit much better performance than previous such implementations., LIPIcs, Vol. 209, 35th International Symposium on Distributed Computing (DISC 2021), pages 56:1-56:4

This paper presents a generic approach for deriving detectably recoverable implementations of many widely-used concurrent data structures. Such implementations are appealing for emerging systems featuring byte-addressable non-volatile main memory (NVMM), whose persistence allows to efficiently resurrect failed threads after crashes. Detectable recovery ensures that after a crash, every executed operation is able to recover and return a correct response, and that the state of the data structure is not corrupted. Our approach, called Tracking, amends descriptor objects used in existing lock-free helping schemes with additional fields that track an operation's progress towards completion and persists these fields in order to ensure detectable recovery. Tracking avoids full-fledged logging and tracks the progress of concurrent operations in a per-thread manner, thus reducing the cost of ensuring detectable recovery. We have applied Tracking to derive detectably recoverable implementations of a linked list, a binary search tree, and an exchanger. Our experimental analysis introduces a new way of analyzing the cost of persistence instructions, not by simply counting them but by separating them into categories based on the impact they have on the performance. The analysis reveals that understanding the actual persistence cost of an algorithm in machines with real NVMM, is more complicated than previously thought, and requires a thorough evaluation, since the impact of different persistence instructions on performance may greatly vary. We consider this analysis to be one of the major contributions of the paper., This paper has appeared in the Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP'22).