Az elmélet átültetése a gyakorlatba, avagy a hallgatói zsebműhold az űrben várakozáson felül teljesít: Theory put into practice or pocket-satellite constructed by students works over expectation

A pocket-satellite called SMOG-P was launched into space on December 6, 2019. It has been working excellently ever since. Its volume is eight times smaller than its predecessor. The size of SMOG-P is 5 x 5 x 5 cm3. The pocket-satellite is equipped with GaAs-based quantum-well solar cell. Of the satellites launched simultaneously, only ours is functional now. According to expert opinions, rival satellites failed in the process of the installation of the solar cell. In this paper, the satellite is shortly described and afterward we focus on the GaAs-based solar cells. Kivonat A SMOG-P nevű zsebműholdat 2019. december 6-án lőtték ki a világűrbe. Azóta is kifogástalanul működik. A zseb-műhold elődjéhez képest nyolcad akkora térfogatú. Mérete 5 x 5 x 5 cm3. A műholdra GaAs-alapú kvantumvölgyes napelem került. A műholdunkkal azonos időben kilőtt berendezések közül csak a miénk működik. A szakértők szerint a vetélytársak a napelem-installáláson buktak el. Jelen dolgozatunkban röviden bemutatjuk a műholdat majd a GaAs napelemre fókuszálunk

Recalibrating fine-grained locking in parallel bucket hash tables

\u3cp\u3eMutual exclusion protects data structures in parallel environments in order to preserve data integrity. A lock being held effectively blocks the execution of all other threads wanting to access the same shared resource until the lock is released. This blocking behavior reduces the level of parallelism causing performance loss. Fine grained locking reduces the contention for the locks resulting in better throughput, however, the granularity, i.e. how many locks to use, is not straightforward. In large bucket hash tables, the best approach is to divide the table into blocks, each containing one or more buckets, and locking these blocks independently. The size of the block, for optimal performance, depends on the time spent within the critical sections, which depends on the table's internal properties, and the arrival intensity of the queries. A queuing model is presented capturing this behavior, and an adaptive algorithm is presented fine-tuning the granularity of locking (the block size) to adapt to the execution environment.\u3c/p\u3