Search for: All records

Synopsis The biological challenges facing humanity are complex, multi-factorial, and are intimately tied to the future of our health, welfare, and stewardship of the Earth. Tackling problems in diverse areas, such as agriculture, ecology, and health care require linking vast datasets that encompass numerous components and spatio-temporal scales. Here, we provide a new framework and a road map for using experiments and computation to understand dynamic biological systems that span multiple scales. We discuss theories that can help understand complex biological systems and highlight the limitations of existing methodologies and recommend data generation practices. The advent of new technologies such as big data analytics and artificial intelligence can help bridge different scales and data types. We recommend ways to make such models transparent, compatible with existing theories of biological function, and to make biological data sets readable by advanced machine learning algorithms. Overall, the barriers for tackling pressing biological challenges are not only technological, but also sociological. Hence, we also provide recommendations for promoting interdisciplinary interactions between scientists. 

Synchronization primitives like barriers heavily impact the performance of parallel programs. As core counts increase and granularity decreases, the value of enabling fast barriers increases. Through the evaluation of the performance of a variety of software implementations of barriers, we found the cost of software barriers to be on the order of tens of thousands of cycles on various incarnations of x64 hardware. We argue that reducing the latency of a barrier via hardware support will dramatically improve the performance of existing applications and runtimes, and would enable new execution models, including those which currently do not perform well on multicore machines. To support our argument, we first present the design, implementation, and evaluation of a barrier on the Intel HARP, a prototype that integrates an x64 processor and FPGA in the same package. This effort gives insight into the potential speed and compactness of hardware barriers, and suggests useful improvements to the HARP platform. Next, we turn to the processor itself and describe an x64 ISA extension for barriers, and how it could be implemented in the microarchitecture with minimal collateral changes. This design allows for barriers to be securely managed jointly between the OS and the application. Finally, we speculate on how barrier synchronization might be implemented on future photonics-based hardware. 

Fast radio bursts (FRBs) are highly dispersed millisecond-duration radio bursts,^[1,2]of which the physical origin is still not fully understood. FRB 20201124A is one of the most actively repeating FRBs. In this paper, we present the collection of 1863 burst dynamic spectra of FRB 20201124A measured with the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The current collection, taken from the observation during the FRB active phase from April to June 2021, is the largest burst sample detected for any FRB so far. The standard PSRFITs format is adopted, including dynamic spectra of the burst, and the time information of the dynamic spectra, in addition, mask files help readers to identify the pulse positions are also provided. The dataset is available in Science Data Bank, with the linkhttps://www.doi.org/10.57760/sciencedb.j00113.00076.