Compilers for accelerator design languages (ADLs) translate high-level languages into application-specific hardware. ADL compilers rely on a hardware control interface to compose hardware units. There are two choices: static control, which relies on cycle-level timing; or dynamic control, which uses explicit signalling to avoid depending on timing details. Static control is efficient but brittle; dynamic control incurs hardware costs to support compositional reasoning. Piezo is an ADL compiler that unifies static and dynamic control in a single intermediate language (IL). Its key insight is that the IL’s static fragment is a refinement of its dynamic fragment: static code admits a subset of the run-time behaviors of the dynamic equivalent. Piezo can optimize code by combining facts from static and dynamic submodules, and it opportunistically converts code from dynamic to static control styles. We implement Piezo as an extension to an existing dynamic ADL compiler, Calyx. We use Piezo to implement a frontend for an existing ADL, a systolic array generator, and a packet-scheduling hardware generator to demonstrate its optimizations and the static–dynamic interactions it enables.

Often, a good explanation for a program’s unexpected behavior is a bug in the programmer’s code. But sometimes, an even better explanation is a bug in the programmer’s mental model of the language or API they are using. Instead of merely debugging our current code (“giving the programmer a fish”), what if our tools could directly debug our mental models (“teaching the programmer to fish”)? In this paper, we apply recent ideas from computational cognitive science to offer a principled framework for doing exactly that. Given a “why?” question about a program, we automatically infer potential misconceptions about the language/API that might cause the user to be surprised by the program’s behavior – and then analyze those misconceptions to provide explanations of the program’s behavior. Our key idea is to formally represent misconceptions as counterfactual (erroneous) semantics for the language/API, which can be inferred and debugged using program synthesis techniques. We demonstrate our framework, WatChat, by building systems for explanation in two domains: JavaScript type coercion, and the Git version control system. We evaluate WatChatJS and WatChatGit by comparing their outputs to experimentally-collected human-written explanations in these two domains: we show that WatChat’s explanations exhibit key features of human-written explanation, unlike those of a state-of-the-art language model.

Modular design is a key challenge for enabling large-scale reuse of hardware modules. Unlike software, however, hardware designs correspond to physical circuits and inherit constraints from them. Timing constraints—which cycle a signal arrives, when an input is read—and structural constraints—how often a multiplier accepts new inputs—are fundamental to hardware interfaces. Existing hardware design languages do not provide a way to encode these constraints; a user must read documentation, build scripts, or in the worst case, a module’s implementation to understand how to use it. We present Filament, a language for modular hardware design that supports the specification and enforcement of timing and structural constraints for statically scheduled pipelines. Filament uses timeline types, which describe the intervals of clock-cycle time when a given signal is available or required. Filament enables safe composition of hardware modules, ensures that the resulting designs are correctly pipelined, and predictably lowers them to efficient hardware.

Traditional web programming involves the creation of two distinct programs: a client-side front-end, a server-side back-end, and a lot of communications boilerplate. An alternative approach is to use a tierless programming model, where a single program describes the behavior of both the client and the server, and the runtime system takes care of communication. Unfortunately, this usually entails adopting a new language and thus abandoning well-worn libraries and web programming tools.

In this paper, we present our ongoing work on Fission, a platform that uses dynamic tier-splitting and dynamic information flow control to transparently run a single JavaScript program across the client and server. Although static tier-splitting has been studied before, our focus on dynamic approaches presents several new challenges and opportunities. For example, Fission supports characteristic JavaScript features such as eval and sophisticated JavaScript libraries like React. Therefore, programmers can reason about the integrity and confidentiality of information while continuing to use common libraries and programming patterns. Moreover, by unifying the client and server into a single program, Fission allows language-based tools, like type systems and IDEs, to manipulate complete web applications. To illustrate, we use TypeScript to ensure that client-server communication does not go wrong.