CLMalloc: contiguous memory management mechanism for large-scale CPU-accelerator hybrid architectures

Abstract

Heterogeneous accelerators play a crucial role in improving computer performance. General-purpose computers reduce the frequent communication between traditional accelerators with separate memory and the host computer through fast communication links. Some high-speed devices such as supercomputers integrate the accelerator and CPU on one chip, and the shared memory is managed by the operating system, which shifts the performance bottleneck from data acquisition to accelerator addressing. Existing memory management mechanisms typically reserve contiguous physical memory locally for peripherals for efficient direct memory access. However, in large computer systems with multiple memory nodes, the accelerator's memory access behavior is limited by the local memory capacity. The difficulty of addressing accelerators across nodes prevents computers from maximizing the benefits of massive memory. This paper proposes a contiguous memory management mechanism for a large-scale CPU-accelerator hybrid architecture (CLMalloc) to simultaneously support the different types of memory requirements of CPU and accelerator programs. In simulation experiments, CLMalloc achieves similar (or even better) performance to the system functions malloc/free. Compared with the DMA-based baseline, the space utilization of CLMalloc is increased by 2×, and the latency is reduced by 80% to 90%.

Estudio de viabilidad de SYCL como modelo de programación unificado para sistemas heterogéneos basados en GPUs en bioinformática

“…La falta de compatibilidad entre estos puede reducir las posibilidades de contar con ciertos componentes clave en un sistema HPC. A su vez, si hay frecuentes transmisiones de información entre la CPU y el acelerador, podría haber un obstáculo para obtener un óptimo rendimiento en todo el sistema [57].…”