Efficient Flow-Sensitive Pointer Analysis on Full-Sparse Memory SSA

Pointer analysis is a fundamental research topic in computer science. It statically determines the potential runtime targets of pointers. Many clients benefit from this information, including compiler optimization, bug detection, security analysis and change impact analysis, etc. As a key dimension in pointer analysis, flow-sensitivity improves its precision by considering program execution order. Ideally, flow-sensitive pointer analysis should be performed by analyzing each program path independently. However, even ignoring the branch conditions, such solution remains intractable and extremely expensive for whole program analysis due to potentially unbounded program paths. Finding the right balance between precision and efficiency in flow-sensitive pointer analysis lies at the heart of pointer analysis. In this thesis, we first introduce an efficient inter-procedural full-sparse memory SSA construction algorithm. Then we improve flow-sensitive pointer analysis based on the memory SSA with the following two contributions: First, Selfs, a region-based selective flow-sensitive pointer analysis, is proposed to allow precision and efficiency trade-offs to be made according to region partitioning. By maintaining flow-sensitivity between regions instead of statements, Selfs is faster than the state-of-the-art full-sparse flow-sensitive analysis while achieving the same precision when used for alias queries. Second, Spas explores the intra-procedural path correlations on top of sparse flow-sensitive and context-sensitive pointer analysis. By using binary decision diagrams to represent the compact path conditions, Spas improves the precision of pointer analysis while only introducing a small overhead

AIGC Empowering Telecom Sector White Paper_chinese

In the global craze of GPT, people have deeply realized that AI, as a transformative technology and key force in economic and social development, will bring great leaps and breakthroughs to the global industry and profoundly influence the future world competition pattern. As the builder and operator of information and communication infrastructure, the telecom sector provides infrastructure support for the development of AI, and even takes the lead in the implementation of AI applications. How to enable the application of AIGC (GPT) and implement AIGC in the telecom sector are questions that telecom practitioners must ponder and answer. Through the study of GPT, a typical representative of AIGC, the authors have analyzed how GPT empowers the telecom sector in the form of scenarios, discussed the gap between the current GPT general model and telecom services, proposed for the first time a Telco Augmented Cognition capability system, provided answers to how to construct a telecom service GPT in the telecom sector, and carried out various practices. Our counterparts in the industry are expected to focus on collaborative innovation around telecom and AI, build an open and shared innovation ecosystem, promote the deep integration of AI and telecom sector, and accelerate the construction of next-generation information infrastructure, in an effort to facilitate the digital transformation of the economy and society

Improved production of docosahexaenoic acid in batch fermentation by newly-isolated strains of Schizochytrium sp. and Thraustochytriidae sp. through bioprocess optimization

Thraustochytrids, rich in docosahexaenoic acid (DHA, C22:6??3), represent a potential source of dietary fatty acids. Yet, the effect of culture conditions on growth and fatty acid composition vary widely among different thraustochytrid strains. Two different thraustochytrid strains, Schizochytrium sp. PKU#Mn4 and Thraustochytriidae sp. PKU#Mn16 were studied for their growth and DHA production characteristics under various culture conditions. Although they exhibited similar fatty acid profiles, PKU#Mn4 seemed a good candidate for industrial DHA fermentation while PKU#Mn16 displayed growth tolerance to a wide range of process conditions. Relative DHA content of 48.5% and 49.2% (relative to total fatty acids), respectively, were achieved on glycerol under their optimal flask culture conditions. Maximum DHA yield (Yp/x) of 21.0% and 18.9% and productivity of 27.6 mg/L-h and 31.9 mg/L-h were obtained, respectively, in 5-L bioreactor fermentation operated with optimal conditions and dual oxygen control strategy. A 3.4- and 2.8-fold improvement of DHA production (g/L), respectively, was achieved in this study. Overall, our study provides the potential of two thraustochytrid strains and their culture conditions for efficient production of DHA-rich oil