Background — High Performance Attached Processors Handicapped By Architecture
The application of high-performance accelerators, notably GPUs, GPGPUs (APUs in AMD terminology) to a variety of computing problems has blossomed over the last decade, resulting in ever more affordable compute power for both horizon and mundane problems, along with growing revenue streams for a growing industry ecosystem. Adding heat to an already active mix, Intel’s Xeon Phi accelerators, the most recent addition to the GPU ecosystem, have the potential to speed adoption even further due to hoped-for synergies generated by the immense universe of x86 code that could potentially run on the Xeon Phi cores.
However, despite any potential synergies, GPUs (I will use this term generically to refer to all forms of these attached accelerators as they currently exist in the market) suffer from a fundamental architectural problem — they are very distant, in terms of latency, from the main scalar system memory and are not part of the coherent memory domain. This in turn has major impacts on performance, cost, design of the GPUs, and the structure of the algorithms:
Performance — The latency for memory accesses generally dictated by PCIe latencies, which while much improved over previous generations, are a factor of 100 or more longer than latency from coherent cache or local scalar CPU memory. While clever design and programming, such as overlapping and buffering multiple transfers can hide the latency in a series of transfers, it is difficult to hide the latency for an initial block of data. Even AMD’s integrated APUs, in which the GPU elements are on a common die, do not share a common memory space, and explicit transfers are made in and out of the APU memory.
As data flows between countries with disparate data protection laws, firms need to ensure the safety of their customer and employee data through regulatory compliance and due diligence. However, multinational organizations often find global data privacy laws exceedingly challenging. To help our clients address these challenges, Forrester developed a research and planning tool called the Data Privacy Heat Map (try the demo version here). Originally published in 2010, the tool leverages in-depth analyses of the privacy-related laws and cultures of 54 countries around the world, helping our clients better strategize their own global privacy and data protection approaches.
Regulation in the data privacy arena is far from static. In the year since we last updated the heat map, we have seen many changes to how countries around the world view and enforce data privacy. Forrester has tracked and rated each of these 54 countries across seven different metrics directly within the tool. Among them, seven countries had their ratings change over the past year. Some of the most significant changes corporations are concerned with involve:
New national omnibus data privacy laws spanning private and/or public industry. Data privacy regulation, when looked at globally, forms a spectrum of maturity beginning with spotty industry or situation-specific laws all the way to omnibus frameworks. As you might expect, responsible corporations prefer to engage in business practices where the data privacy laws are clearly-defined and transparent. For instance, countries such as Brazil and China are in the process of moving towards potential omnibus laws which will replace a multitude of sectoral and situation-based laws. Other countries, such as Colombia and Singapore, have recently passed far-reaching omnibus laws, also replacing a patchwork of prior sectoral laws.