What does Analytical Processing Unit (APU) mean?
An Analytical Processing Unit (APU) is a dedicated unit System on a chip (SoCs) to optimize data analysis in column-oriented databases, as well as to increase analytical workloads. Each APU consists of multiple massively parallel multi-core processors
An APU can be thought of as an accelerator for distributed computing and I/O processes. Just as Graphics Processing Units (GPUs) are used to augment compute-intensive workloads for deep learning applications, APUs can be used to augment compute-intensive workloads for Big Data analytics. Cloud and on-premises data.
In addition to accelerating computation, the APU architecture significantly reduces the need for DRAM bandwidth, which effectively increases bandwidth to memory and improves memory capacity. Since multiple I/O operations are performed in parallel in dedicated hardware, ETL (extract, transform, load) workloads can be dramatically accelerated. A single server with a few APUs, for example, can replace multiple processor racks, while dramatically saving space, reducing energy costs, and exponentially improving runtimes.
Techopedia Explains Analytical Processing Unit (APU)
Big Data is exploding and analytics is increasingly becoming the cornerstone of all successful organizations. In the next few years, database analysis and processing is expected to be an even bigger workload than artificial intelligence (AI) in terms of dollars spent. This is why industries are looking for solutions to speed up database analysis. This will be the key to gaining or maintaining a competitive advantage.
The problem is that current processing units are not designed to handle today’s workloads. As data gets larger, caches are less efficient, and memory access for analytics applications can consume a disproportionate amount of power. Some vendors have tried using Field Programmable Gate Arrays (FPGAs) as accelerators for big data analytics workloads, but the results have been mixed.
Over time, it is becoming increasingly clear that application-specific integrated circuits (ASICs), including analytical processing units, will play an important role in reducing bottlenecks for specific types of workloads. working in the cloud. The challenge for vendors in this market space will be ensuring that acceleration hardware is compatible with legacy software and existing frameworks.