An experimental platform to study massively multi-core processor support for active data storage services

该申请寻求资助一个实验平台，以支持以下三个假设的探索。首先，我们相信主动存储技术可以高效、透明地与大规模多核计算资源集成，以加速医学图像分析和生物信息学等领域的数据密集型应用程序的执行。第二个假设是，这些大规模多核处理器的计算能力不仅可以用来加速专门的应用程序，还可以用来加速、增强或降低通用存储系统的成本。廉价的计算可用于支持影响存储系统的可靠性、安全性或性能的核心技术，例如通过使用擦除编码、加密或动态数据压缩。最后，第三个假设是，一个特定类别的商品多核处理器，即图形处理单元（GPU），可以有效地用于上述背景下。

This application seeks funding for an experimental platform to support the exploration of the following three hypotheses. First, we believe that active storage techniques can be efficiently and transparently integrated with massively multi-core compute resources to accelerate the execution of data-intensive applications in fields as diverse as medical image analysis and bioinformatics. The second hypothesis is that the computational power of these massively multi-core processors can be harnessed not only to accelerate specialized applications, but also to accelerate, enhance, or reduce the cost of generic storage systems. Inexpensive computation can be used to support core techniques that impact storage systems' reliability, security, or performance by using, for example, erasure coding, encryption, or on-the-fly data compression. Finally, the third hypothesis is that a specific class of commodity multi-core processors, namely graphical processing units (GPUs), can be effectively used in the above context.