New hardware technology such as systems- and networks-on-chip (SOCs and NOCs), switchless network fabrics, silicon photonics, and RDMA, are redefining the landscape of data center computing, enabling interconnecting thousands of cores at high speed at the scale of today's racks. We refer to this new class of hardware as rack-scale computers (RSCs) because the rack is increasingly replacing the individual server as the basic building block of modern data centers. Early examples of RSCs have already appeared on the market from manufactures such as AMD SeaMicro, HP, and Intel and similar solutions are being deployed at large-scale companies such as Facebook and Microsoft.
These new hardware trends challenge traditional assumptions and force us to rethink existing software architectures. The goal of the Rack-scale Computing project is to perform a cross-layer redesign of the way the hardware, OS, storage and network stacks, and applications are built and interact in that new context. The key insight is that by co-designing different layers of the stack, it is possible to achieve both better performance and higher efficiency.
In our early CamCube work, we explored the opportunities provided by distributed switching fabrics and the benefits of tightly integrating applications and networks. Our on-going efforts are focused on supporting efficient access to rack-scale resources. In the Pelican project we are designing a cost-effective storage appliance for cold data. Projects FARM and gRANA explore the design space for efficient management of memory and network resources within the rack. Finally, in the DRackAr project, we are working on solutions to automate the design of rack-scale computers.
Server-centric fabric for data centers
Designing next-generation RAck-scale Network Architecture
Rack-scale storage for cold data
Fast Available Remote Memory
Automated design of rack-scale computers
- Paolo Costa, Hitesh Ballani, and Dushyanth Narayanan, Rethinking the Network Stack for Rack-scale Computers, in 6th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud'14), USENIX, June 2014
- Aleksandar Dragojević, Dushyanth Narayanan, Orion Hodson, and Miguel Castro, FaRM: Fast Remote Memory, in 11th USENIX Symposium on Networked Systems Design and Implementation (NSDI 2014), USENIX, 4 April 2014
- Raja Appuswamy, Christos Gkantsidis, Dushyanth Narayanan, Orion Hodson, and Antony Rowstron, Scale-up vs Scale-out for Hadoop: Time to rethink?, ACM Symposium on Cloud Computing, 2 October 2013
- Paolo Costa, Austin Donnelly, Greg O'Shea, and Antony Rowstron, CamCubeOS: A Key-based Network Stack for 3D Torus Cluster Topologies, in The 22nd ACM International Symposium on High Performance Parallel and Distributed Computing (HPDC'13), ACM Press, New York, NY, US, June 2013
- Paolo Costa, Austin Donnelly, Antony Rowstron, and Greg O'Shea, Camdoop: Exploiting In-network Aggregation for Big Data Applications, in 9th USENIX Symposium on Networked Systems Design and Implementation (NSDI'12), USENIX, April 2012
- Hussam Abu-Libdeh, Paolo Costa, Antony Rowstron, Austin Donnelly, and Greg O'Shea, Symbiotic Routing in Future Data Centers, ACM SIGCOMM, August 2010