Engineering topics

Dillow, David A

Publications and source records attributed to Dillow, David A.

4 records

DOE OSTI2014

Coordinated garbage collection for raid array of solid state disks

An optimized redundant array of solid state devices may include an array of one or more optimized solid-state devices and a controller coupled to the solid-state devices for managing the solid-state devices. The controller may be configured to globally coordinate the garbage collection activities of each of said optimized solid-state devices, for instance, to minimize the degraded performance time and increase the optimal performance time of the entire array of devices.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Coordinating Garbage Collection for Arrays of Solid-state Drives

Although solid-state drives (SSDs) offer significant performance improvements over hard disk drives (HDDs) for a number of workloads, they can exhibit substantial variance in request latency and throughput as a result of garbage collection (GC). When GC conflicts with an I/O stream, the stream can make no forward progress until the GC cycle completes. GC cycles are scheduled by logic internal to the SSD based on several factors such as the pattern, frequency, and volume of write requests. When SSDs are used in a RAID with currently available technology, the lack of coordination of the SSD-local GC cycles amplifies this performance variance. We propose a global garbage collection (GGC) mechanism to improve response times and reduce performance variability for a RAID of SSDs. We include a high-level design of SSD-aware RAID controller and GGC-capable SSD devices and algorithms to coordinate the GGC cycles. We develop reactive and proactive GC coordination algorithms and evaluate their I/O performance and block erase counts for various workloads. Our simulations show that GC coordination by a reactive scheme improves average response time and reduces performance variability for a wide variety of enterprise workloads. For bursty, write-dominated workloads, response time was improved by 69% and performance variability was reduced by 71%. We show that a proactive GC coordination algorithm can further improve the I/O response times by up to 9% and the performance variability by up to 15%. We also observe that it could increase the lifetimes of SSDs with some workloads (e.g. Financial) by reducing the number of block erase counts by up to 79% relative to a reactive algorithm for write-dominant enterprise workloads.

Flash Memory↗

DOE OSTI2013

SeaStar Unchained: Multiplying the Performance of the Cray SeaStar Network

The Oak Ridge Leadership Computing Facility (OLCF) supports many different systems and many differ- ent interconnects. The only common programming interfaces across these systems are BSD Sockets and MPI. Due to the design assumptions such as implicit buffering leading to extra copies, Sockets performance is almost universally lower than the native interface. Even in the cases that Sockets provides similar bandwidth as the native interface, it suffers from excessive CPU usage. MPI is the de-facto interface for intra- job communication, but is difficult to use between jobs and provides no ability to communicate with service nodes or off- system nodes (e.g. for I/O forwarding). We have developed the Common Communication Interface (CCI), a programming interface that exposes the advances in interconnect hardware, notably Remote Direct Memory Access (RDMA) and operating system (OS) bypass, while imposing as little overhead as possible. This API directly supports inter-job as well as off- system communication. CCI is a lightweight abstraction layer that provides point-to-point messaging and remote memory access. The Cray SeaStar ASIC, with its programmable embedded processor, provides an excellent platform to investigate the properties of various network protocols and programming interfaces. This paper describes our native implementation CCI on the SeaStar platform, and details how we implemented full OS bypass for common operations. We demonstrate a 30% to 50% reduction in latency, more than a six-fold increase in message injection rate, and an almost 7x improvement in bandwidth for small message sizes when compared to the generic Cray Portals implementation.

Dillow, David A↗

DOE OSTI2013

Asynchronous Object Storage with QoS for Scientific and Commercial Big Data

This paper presents our design for an asynchronous object storage system intended for use in scientific and commercial big data workloads. Use cases from the target workload do- mains are used to motivate the key abstractions used in the application programming interface (API). The architecture of the Scalable Object Store (SOS), a prototype object stor- age system that supports the API s facilities, is presented. The SOS serves as a vehicle for future research into scalable and resilient big data object storage. We briefly review our research into providing efficient storage servers capable of providing quality of service (QoS) contracts relevant for big data use cases.

Cloud Storage↗