Context: Secure Multiparty Computation (MPC) refers to a family of cryptographic techniques where mutually untrusting parties may compute functions of their private inputs while revealing only the function output. Inquiry: It can be hard to program MPCs correctly and efficiently using existing languages and frameworks, especially when they require coordinating disparate computational roles. How can we make this easier? Approach: We present Symphony, a new functional programming language for MPCs among two or more parties. Symphony starts from the single-instruction, multiple-data (SIMD) semantics of prior MPC languages, in which each party carries out symmetric responsibilities, and generalizes it using constructs that can coordinate many parties. Symphony introduces **first-class shares** and **first-class party sets** to provide unmatched language-level expressive power with high efficiency. Knowledge: Developing a core formal language called $λ$-Symphony, we prove that the intuitive, generalized SIMD view of a program coincides with its actual distributed semantics. Thus the programmer can reason about her programs by reading them from top to bottom, even though in reality the program runs in a coordinated fashion, distributed across many machines. We implemented a prototype interpreter for Symphony leveraging multiple cryptographic backends. With it we wrote a variety of MPC programs, finding that Symphony can express optimized protocols that other languages cannot, and that in general Symphony programs operate efficiently. [ full abstract at https://doi.org/10.22152/programming-journal.org/2023/7/14 ]