numam-spdk/doc/about.md
Ben Walker d5d24e3e9d doc: Add an overview page for the project
Change-Id: I21b793c27aa7f24ffa1235c4a2c43d594148a689
Signed-off-by: Ben Walker <benjamin.walker@intel.com>
Reviewed-on: https://review.gerrithub.io/392982
Tested-by: SPDK Automated Test System <sys_sgsw@intel.com>
Reviewed-by: Jim Harris <james.r.harris@intel.com>
Reviewed-by: Paul Luse <paul.e.luse@intel.com>
Reviewed-by: Daniel Verkamp <daniel.verkamp@intel.com>
2018-01-05 12:47:01 -05:00

1.9 KiB

What is SPDK?

The Storage Performance Development Kit (SPDK) provides a set of tools and libraries for writing high performance, scalable, user-mode storage applications. It achieves high performance through the use of a number of key techniques:

  • Moving all of the necessary drivers into userspace, which avoids syscalls and enables zero-copy access from the application.
  • Polling hardware for completions instead of relying on interrupts, which lowers both total latency and latency variance.
  • Avoiding all locks in the I/O path, instead relying on message passing.

The bedrock of SPDK is a user space, polled-mode, asynchronous, lockless NVMe driver. This provides zero-copy, highly parallel access directly to an SSD from a user space application. The driver is written as a C library with a single public header. See @ref nvme for more details.

SPDK further provides a full block stack as a user space library that performs many of the same operations as a block stack in an operating system. This includes unifying the interface between disparate storage devices, queueing to handle conditions such as out of memory or I/O hangs, and logical volume management. See @ref bdev for more information.

Finally, SPDK provides NVMe-oF, iSCSI, and vhost servers built on top of these components that are capable of serving disks over the network or to other processes. The standard Linux kernel initiators for NVMe-oF and iSCSI interoperate with these targets, as well as QEMU with vhost. These servers can be up to an order of magnitude more CPU efficient than other implementations. These targets can be used as examples of how to implement a high performance storage target, or used as the basis for production deployments.