: A Lightweight

Stencil Computation at the Intersection of AI and HPC

Tensor compilers such as TinyTC and OpenAI Triton were originally developed for AI workloads, but the same tiling and memory abstractions can be applied to implement efficient high-order stencils for scientific and industrial applications. We demonstrate this for an 8th-order, 25-point acoustic stencil with boundary co...

PSyclone 3: A source-to-source Fortran compiler for developing maintainable and performance-portable HPC applications

GPU-Accelerated Presolving for Linear Programming

Simple design principles that avoid severe load imbalance and expose parallelism in reductions that appear inherently sequential are described and implemented in cuPSLP, a GPU-accelerated version of PSLP, a CPU-based presolver that is itself several times faster than a state-of-the-art commercial presolver.

SimDSL: A Domain-Specific Language for Large-Scale GPU-Resident Simulation

These findings demonstrate that high-level ECS simulation programs can be compiled into efficient GPU execution without requiring users to manually implement and coordinate low-level kernels.

CIA: Composable Instruction-Based Accelerators

The use of custom instructions is a common approach to accelerate domain-specific problems. However, it is difficult to reuse instruction-based accelerators in new systems — for example, if multiple accelerators from past systems are merged into a single SoC, they may have colliding opcodes. Fixing this requires opcode...

GPU implementation of a resource-constrained virtual machine

This paper presents an OpenMP-style parallelism API for Uxntal, the stack-based assembly-style language for the Uxn platform, and demonstrates that exemplar code using this API can run at comparable performance even on an integrated GPU.