"Data-intensive" aplikazio baten fitxategi kudeaketa aldatzen memoria mugak gainditzeko
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Aplikazio zientifikoek RAM memoria izugarria behar izaten dute sarrerako datuak handiak direnean hauekprozesatu ahal izateko. Biologiaren arloan -eta genetikaren atalean zehazki- datu tamaina sorta handia dago:kilobyte gutxi batzuetatik ehunaka gigabyte-ko datu-sekuentziak aurki daitezke.Burrows-Wheeler Alligner(BWA) aplikazioak DNA irakurketak lerrokatzen ditu, gene zehatzak eta genoma baten barne hauen kokapena/kaurkitzeko. Horretarako, memorian kargatzen ditu bai bilatu nahi diren irakurketak eta bai konparatzeke dagoengenoma. Tamaina handiekin lan egiterakoan gerta daiteke ordenagailuak behar adina memoria ez izatea. Lanhonetan BWA aplikazioaren memoria kudeaketa aztertu eta aldatu egingo da sarrera handiagoak prozesatu ahalizateko baliabide mugatuak dituzten konputagailuetan.
Scientific applications tend to be hard on system memory as to process big input data. In the field of biology-concretely on the genomics field- there is a high variety of input data sizes: readings can be found with a sizerange from a few kilobytes to hundreds of gigabytes. Burrows-Wheeler Aligner (BWA) is an application thataligns DNA readings in order to find specific genes and their exact location in a genome. The application loadsboth the readings that are to be looked for and the big genome into memory. The computer might not have thesufficient amount of memory to process big input genomes. In this work, the memory management found in BWAwill be analyzed and modified in order to allow processing bigger readings in computers with limited resources.
Scientific applications tend to be hard on system memory as to process big input data. In the field of biology-concretely on the genomics field- there is a high variety of input data sizes: readings can be found with a sizerange from a few kilobytes to hundreds of gigabytes. Burrows-Wheeler Aligner (BWA) is an application thataligns DNA readings in order to find specific genes and their exact location in a genome. The application loadsboth the readings that are to be looked for and the big genome into memory. The computer might not have thesufficient amount of memory to process big input genomes. In this work, the memory management found in BWAwill be analyzed and modified in order to allow processing bigger readings in computers with limited resources.
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BWA, C programazio lengoaia, Linux, memoria kudeaketa, mmap, BWA, C programming language, Linux, memory management, mmap