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I like the idea of chapel, but I'm not sure I agree with a lot of their design choices. Some of the parallelization features seem like they just copied OpenMP w

I like the idea of chapel, but I'm not sure I agree with a lot of their design choices. Some of the parallelization features seem like they just copied OpenMP without meaningfully improving on it. They also kept exceptions, which are generally on their way out, especially in compiled languages (Go, Rust, Zig, and while they exist in modern C++ they are introducing more ways to not use them). I think a new HPC language is possible but I'm not sure this is the one

bradcray 6mo ago
I disagree with the characterization that Chapel's parallelization features copied OpenMP without improving upon it: * Chapel's support for task parallelism predates OpenMP's (~2004 vs. ~2007, where Wikipedia cites Chapel's tasks as being inspiration for OpenMP's, along with Cilk and X10). Chapel's tasks are also arguably more general-purpose (akin to threads) in terms of their ability to synchronize, support data-driven producer/consumer patterns, etc. * Chapel's forall loops are similar to OpenMP's loop-based parallelization pragmas, though OpenMP wasn't a source of inspiration in their design. Where OpenMP pragmas select from a menu of parallelization strategies baked into the specification and implementation, Chapel's forall loops invoke user-defined parallel iterators that permit abstracting a particular parallel pattern (say, multidimensional tiled iteration or tree traversal) into a named subroutine. These iterators can optionally be made methods of data structures and/or placed within libraries, and can be re-used across a program or multiple programs. One such library, DynamicIters, was community-contributed and specifically inspired by OpenMP's dynamic and guided scheduling strategies. * Chapel supports parallel zippered iteration, in which two or more data structures and/or parallel iterators can be traversed in a coordinated manner. * Chapel's parallelism can span multiple compute nodes via its shared namespace, which obviates the need for explicit communication; whereas OpenMP is limited to a single compute node or process unless mixed with MPI, SHMEM, or the like (and even then, OpenMP doesn't gain a cross-node view of parallel computation). * In Chapel, parallelism can be expressed implicitly, for example, by passing an array argument to a subroutine or operator that is expecting a scalar (e.g., `var B = sin(A);` or `var C = A + B;`).

bradcray 6mo ago

I disagree with the characterization that Chapel's parallelization features copied OpenMP without improving upon it: * Chapel's support for task parallelism predates OpenMP's (~2004 vs. ~2007, where Wikipedia cites Chapel's tasks as being inspiration for OpenMP's, along with Cilk and X10). Chapel's tasks are also arguably more general-purpose (akin to threads) in terms of their ability to synchronize, support data-driven producer/consumer patterns, etc. * Chapel's forall loops are similar to OpenMP's loop-based parallelization pragmas, though OpenMP wasn't a source of inspiration in their design. Where OpenMP pragmas select from a menu of parallelization strategies baked into the specification and implementation, Chapel's forall loops invoke user-defined parallel iterators that permit abstracting a particular parallel pattern (say, multidimensional tiled iteration or tree traversal) into a named subroutine. These iterators can optionally be made methods of data structures and/or placed within libraries, and can be re-used across a program or multiple programs. One such library, DynamicIters, was community-contributed and specifically inspired by OpenMP's dynamic and guided scheduling strategies. * Chapel supports parallel zippered iteration, in which two or more data structures and/or parallel iterators can be traversed in a coordinated manner. * Chapel's parallelism can span multiple compute nodes via its shared namespace, which obviates the need for explicit communication; whereas OpenMP is limited to a single compute node or process unless mixed with MPI, SHMEM, or the like (and even then, OpenMP doesn't gain a cross-node view of parallel computation). * In Chapel, parallelism can be expressed implicitly, for example, by passing an array argument to a subroutine or operator that is expecting a scalar (e.g., `var B = sin(A);` or `var C = A + B;`).