Exo 2: Transforming High-Performance Computing with Less Code and More Control

In the competitive arena of high-performance computing (HPC), titans like NVIDIA have historically dominated with complex libraries that form the backbone of modern AI systems. However, an intriguing innovation from the Massachusetts Institute of Technology (MIT) points to a potential shift in this paradigm. Enter Exo 2, a novel programming language poised to dramatically reduce the coding workload without sacrificing performance.

Breaking Barriers in High-Performance Computing

Traditionally, crafting cutting-edge HPC libraries demands significant investment in skilled programmers who develop extensive lines of code. Yet researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have demonstrated Exo 2’s prowess in matching state-of-the-art libraries with merely a fraction of the code. This “user-schedulable language” (USL) empowers developers with unprecedented control over compiler-generated code, diverging from the conventional reliance on opaque compiler processes for optimization.

Unleashing Efficiency with Exo 2

A key limitation with existing USLs, including its predecessor Exo, was the rigid approach to scheduling that hampered code reuse across different core components or kernels of HPC libraries. Exo 2 revolutionizes this aspect by enabling external definition of scheduling operations, promoting the creation of reusable scheduling libraries. Lead author and Ph.D. student Yuka Ikarashi from MIT explains that Exo 2 can slash scheduling code volume by up to 100-fold while maintaining high-performance benchmarks across various platforms and hardware.

The bottom-up automation approach of Exo 2 allows performance engineers to develop bespoke scheduling libraries tailored to maximize hardware capabilities. This method not only enhances efficiency by minimizing coding efforts but also leverages reusable schedules applicable to diverse applications and hardware configurations. A significant feature, “Cursors,” ensures stable reference points within scheduling functions, crucial for maintaining coherent schedule encapsulation in library operations.

The Road Ahead for Exo 2

Exo 2 marks a significant milestone in making USLs more extensible, allowing for growth through library implementations suited to specific optimization needs and domains. Its architecture aims not only to streamline high-level optimization but also to ensure the resulting object code retains its functional integrity, supported by safe programming primitives. Moving forward, the MIT team intends to expand Exo 2’s reach, including GPU support, and advance compiler analysis to enhance correctness, reduce compilation time, and increase expressivity.

Key Takeaways

By drastically reducing coding requirements while maximizing efficiency, Exo 2 signifies a pivotal advancement in the HPC landscape. By granting developers more control over code optimization processes, it positions itself to reshape conventional computing paradigms, offering a more efficient, adaptable approach to developing robust computing libraries. As Exo 2 evolves, it promises not only to broaden its capabilities across various hardware accelerators but also to expand the possibilities within the realm of HPC—and potentially beyond.