Hardware accelerators breathe a sigh of relief as the latest programming language Exo enters the market. Currently, the configuration of the computer chips is going through a revolution with the emergence of hardware accelerators, which are basically a bunch of silicon microchips completing a narrow set of tasks a lot faster than a general-purpose CPU.
With hardware acceleration, a special integrated circuit or microprocessor does one specific task or a narrow set of related jobs. The circuit's design is not wasted on anything else, and this provides a significant performance advantage. However, even though these hardware accelerators can run certain tasks orders of magnitude faster than CPUs, they cannot be used out of the box. Software needs to efficiently use accelerators' instructions to make it compatible with the entire application system. This translates to a lot of engineering work that they would have to be maintained for a new chip that you're compiling code to, with any programming language.
To save the day, MIT scientists have created a new programming language called "Exo" for writing high-performance code on hardware accelerators. Exo helps low-level performance engineers transform very simple programs that specify what they want to compute, into very complex programs that do the same thing as the specification, but much, much faster by using these special accelerator chips. Engineers, for example, can use Exo to turn a simple matrix multiplication into a more complex program, which runs orders of magnitude faster by using these special accelerators. Unlike other programming languages and compilers, Exo is built around a concept called "Exocompilation."
With Exocompilation, the performance engineer is back in the driver's seat. Responsibility for choosing which optimizations to apply, when, and in what order is externalized from the compiler, back to the performance engineer. This way, they don't have to waste time fighting the compiler on the one hand, or doing everything manually on the other. At the same time, Exo takes responsibility for ensuring that all of these optimizations are correct. As a result, the performance engineer can spend their time improving performance, rather than debugging the complex, optimized code.
What makes Exo better than the previous languages is that instead of writing a bunch of messy C++ code to compile for a new accelerator, Exo gives you an abstract, uniform way to write down the 'shape' of the hardware you want to target. Then you can reuse the existing Exo compiler to adapt to that new description instead of writing something entirely new from scratch. The potential impact of work like this is enormous: If hardware innovators can stop worrying about the cost of developing new compilers for every new hardware idea, they can try out and ship more ideas. The industry could break its dependence on legacy hardware that succeeds only because of an ecosystem lock-in and despite its inefficiency.
Another key part of Exocompilation is that performance engineers can describe the new chips they want to optimize for, without having to modify the compiler. Traditionally, the definition of the hardware interface is maintained by the compiler developers, but with most of these new accelerator chips, the hardware interface is proprietary. Companies have to maintain their own copy (fork) of a whole traditional compiler, modified to support their particular chip. This requires hiring teams of compiler developers in addition to the performance engineers.
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