Domain-specific languages provide a promising path to automatically compile high-level code to parallel, heterogeneous, and distributed hardware. However, in practice high performance DSLs still require considerable software expertise to develop and force users into tool-chains that hinder prototyping and debugging. To address these problems, we present Forge, a new meta DSL for declaratively specifying high performance embedded DSLs. Forge provides DSL authors with high-level abstractions (e.g., data structures, parallel patterns, effects) for specifying their DSL in a way that permits high performance. From this high-level specification, Forge automatically generates both a naïve Scala library implementation of the DSL and a high performance version using the Delite DSL framework. Users of a Forge-generated DSL can prototype their application using the library version, and then switch to the Delite version to run on multicore CPUs, GPUs, and clusters without changing the application code. Forge-generated Delite DSLs perform within 2x of hand-optimized C++ and up to 40x better than Spark, an alternative high-level distributed programming environment. Compared to a manually implemented Delite DSL, Forge provides a factor of 3-6x reduction in lines of code and does not sacrifice any performance. Furthermore, Forge specifications can be generated from existing Scala libraries, are easy to maintain, shield DSL developers from changes in the Delite framework, and enable DSLs to be retargeted to other frameworks transparently.

Real-world databases often have extremely complex schemas. With thousands of entity types and relationships, each with a hundred or so attributes, it is extremely difficult for new users to explore the data and formulate queries. Schema free query interfaces (SFQIs) address this problem by allowing users with no knowledge of the schema to submit queries. We postulate that SFQIs should deliver the same answers when given alternative designs for the same underlying data set. In this paper, we introduce and formally define design independence, which captures this property for SFQIs. We establish a theoretical framework to measure the amount of design independence provided by an SFQI. We show that most current SFQIs provide a very limited degree of design independence. We also show that SFQIs based on the statistical properties of data can provide design independence when the changes in the schema do not introduce or remove redundancy in the data. We propose a novel XML SFQI called Duplication Aware Coherency Ranking (DA-CR) based on information-theoretic relationships among the data items in the database, and prove that DA-CR is design independent. Our extensive empirical study using three real-world data sets shows that the average case design independence of current SFQIs is considerably lower than that of DA-CR. We also show that the ranking quality of DA-CR is better than or equal to that of current SFQI methods.