HISQ inverter on Intel Xeon Phi and NVIDIA GPUs

Understand

The runtime of a Lattice QCD simulation is dominated by a small kernel, which calculates the product of a vector by a sparse matrix known as the "Dslash" operator.

• Therefore, this kernel is frequently optimized for various HPC architectures.
• In this contribution we compare the performance of the Intel Xeon Phi to current Kepler-based NVIDIA Tesla GPUs running a conjugate gradient solver.
• By exposing more parallelism to the accelerator through inverting multiple vectors at the same time we obtain a performance 250 GFlop/s on both architectures.