Computational models are an essential tool for the design, characterization, and discovery
of novel materials. Computationally hard tasks in materials science stretch the limits of …

The Single Instruction Multiple Data (SIMD) architecture, supported by various high-
performance computing platforms, efficiently utilizes data-level parallelism. The SIMD model …

Performance portability is becoming more-and-more important as next-generation high
performance computing systems grow increasingly diverse and heterogeneous. Several …

To HPC and AI analytics engineers, math primitives such as basic linear algebra
subprograms or random number generators are key functionality that have highly optimized …

As the computing hardware landscape gets more diverse, and the complexity of hardware
grows, the need for a general purpose parallel programming model capable of developing …

This paper addresses the need for automatic and efficient generation of host driver code for
arbitrary custom AXI-based accelerators targeting linear algebra algorithms, an important …

This paper presents the performance portable implementation of a kinetic plasma simulation
code with C++ parallel algorithm to run across multiple CPUs and GPUs. Relying on the …

SYCL is a modern high-level C++ programming interface which excels at expressing data
parallelism for heterogeneous hardware platforms in a programmer-friendly way, and is …

Providing convenient APIs and notations for data parallelism which remain accessible for
programmers while still providing good performance has been a long-term goal of …

We present the results of a first SYCL vs CUDA performance assessment for the case of the
three-dimensional XCA-Flow subsurface Extended Cellular Automata model. A grid domain …