A very interesting project developed by Zachary DeVito et al at Stanford University:
Terra is a new low-level system programming language that is designed to interoperate seamlessly with the Lua programming language:
-- This top-level code is plain Lua code.
print("Hello, Lua!")
-- Terra is backwards compatible with C
-- we'll use C's io library in our example.
C = terralib.includec("stdio.h")
-- The keyword 'terra' introduces
-- a new Terra function.
terra hello(argc : int, argv : &rawstring)
-- Here we call a C function from Terra
C.printf("Hello, Terra!\n")
return 0
end
-- You can call Terra functions directly from Lua
hello(0,nil)
-- Or, you can save them to disk as executables or .o
-- files and link them into existing programs
terralib.saveobj("helloterra",{ main = hello })
Like C, Terra is a simple, statically-typed, compiled language with manual memory management. But unlike C, it is designed from the beginning to interoperate with Lua. Terra functions are first-class Lua values created using the terra keyword. When needed they are JIT-compiled to machine code.
Seems as if the target use case is high-performance computing. The team has also released a related paper, titled Terra: A Multi-Stage Language for High-Performance Computing:
High-performance computing applications, such as auto-tuners and domain-specific languages, rely on generative programming techniques to achieve high performance and portability. However, these systems are often implemented in multiple disparate languages and perform code generation in a separate process from program execution, making certain optimizations difficult to engineer. We leverage a popular scripting language, Lua, to stage the execution of a novel low-level language, Terra. Users can implement optimizations in the high-level language, and use built-in constructs to generate and execute high-performance Terra code. To simplify meta-programming, Lua and Terra share the same lexical environment, but, to ensure performance, Terra code can execute independently of Lua’s runtime. We evaluate our design by reimplementing existing multi-language systems entirely in Terra. Our Terra-based auto-tuner for BLAS routines performs within 20% of ATLAS, and our DSL for stencil computations runs 2.3x faster than hand-written C.
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