Michael Forster – författare

Die Idee zu diesem Buch entstand nach der ersten gemeinsamen Hopfenernte einer chinesischen Medizinerin und eines Hopfenbauern. Leidenschaftlich werden die Leser:innen durch Vergangenheit und Zukunft des Hopfens geführt. Er verändert die Welt und ist ein internationales Milliardengeschäft. 2026 ist der Hopfenanbau in Deutschland als immaterielles Kulturgut ausgezeichnet worden. Die Hallertau ist das weltgrößte Hopfenanbaugebiet. Weltweit laufen Studien über Hopfen. Er könnte sich zum Game-Changer der Zukunft entwickeln als Antibiotikum und Tumortherapeutikum, der nicht nur Bier würzt, sondern sich positiv auswirkt auf Anti-Aging, Longevity, Langlebigkeit, Gewichtsabnahme, Fruchtbarkeit, Unsterblichkeit, Verjüngung. Dank chinesischer Kräutermedizin wird Hopfen aus einer anderen Perspektive erklärt.

Hops are changing the world. Hops in beer is a global business worth billions - and could prove to be one of the most important active ingredients of the future. The idea for this book arose following the first joint hop harvest by a Chinese doctor and a hop farmer. Evi Strohm and Michael Forster guide readers passionately through the past and future of this extraordinary plant - in a personal yet well-informed manner. Studies worldwide are investigating their potential in medicine. Hops could become a game-changer: as an antibiotic, in tumour therapy, and with possible positive effects on longevity, metabolism, fertility and rejuvenation. In 2026, hop cultivation in Germany was recognised as an intangible cultural heritage. This tradition has its roots in the Hallertau, the world's largest hop-growing region - yet the significance of hops today extends far beyond that. Through the lens of Chinese herbal medicine, hops are being reimagined entirely explained in an accessible way and made available to everyone.

Numerical programs often use parallel programming techniques such as OpenMP to compute the program''s output values as efficient as possible. In addition, derivative values of these output values with respect to certain input values play a crucial role. To achieve code that computes not only the output values simultaneously but also the derivative values, this work introduces several source-to-source transformation rules. These rules are based on a technique called algorithmic differentiation. The main focus of this work lies on the important reverse mode of algorithmic differentiation. The inherent data-flow reversal of the reverse mode must be handled properly during the transformation. The first part of the work examines the transformations in a very general way since pragma-based parallel regions occur in many different kinds such as OpenMP, OpenACC, and Intel Phi. The second part describes the transformation rules of the most important OpenMP constructs.