Abstract:
The present system enables more efficient I/O processing by providing a mechanism for maintaining data within the locality of reference. One or more accelerator modules may be implemented within a solid state storage device (SSD). The accelerator modules form a caching storage tier that can receive, store and reproduce data. The one or more accelerator modules may place data into the SSD or hard disk drives based on parameters associated with the data.
Abstract:
The present system enables more efficient I/O processing by providing a mechanism for maintaining data within the locality of reference. One or more accelerator modules may be implemented within a solid state storage device (SSD). The accelerator modules form a caching storage tier that can receive, store and reproduce data. The one or more accelerator modules may place data into the SSD or hard disk drives based on parameters associated with the data.
Abstract:
A scalable software stack is disclosed. In particular, the present disclosure provides a system and a method directed at allocating logical ownership of memory locations in a shared storage device among two or more associated compute devices that have access to the storage device. The logical ownership allocation can minimize potential conflicts between two simultaneous accesses occurring within the same memory location of the storage device.
Abstract:
The present technology provides a two step process for providing a linearized dynamic storage pool. First, physical storage devices are abstracted. The physical storage devices used for the pool are divided into extents, grouped by storage class, and stripes are created from data chunks of similar classified devices. A virtual volume is then provisioned from and the virtual volume is divided into virtual stripes. A volume map is created to map the virtual stripes with data to the physical stripes, linearly mapping the virtual layout to the physical capacity to maintain optimal performance.
Abstract:
In high performance computing, the potential compute power in a data center will scale to and beyond a billion-billion calculations per second (“Exascale” computing levels). Limitations caused by hierarchical memory architectures where data is temporarily stored in slower or less available memories will increasingly limit high performance computing systems from approaching their maximum potential processing capabilities. Furthermore, time spent and power consumed copying data into and out of a slower tier memory will increase costs associated with high performance computing at an accelerating rate. New technologies, such as the novel Zero Copy Architecture disclosed herein, where each compute node writes locally for performance, yet can quickly access data globally with low latency will be required. The result is the ability to perform burst buffer operations and in situ analytics, visualization and computational steering without the need for a data copy or movement.
Abstract:
The present system enables more efficient I/O processing by providing a mechanism for maintaining data within the locality of reference. One or more accelerator modules may be implemented within a solid state storage device (SSD). The accelerator modules form a caching storage tier that can receive, store and reproduce data. The one or more accelerator modules may place data into the SSD or hard disk drives based on parameters associated with the data.