Engineering topics

DeMar, Phil

Publications and source records attributed to DeMar, Phil.

23 records · Page 2

DOE OSTI2011

G-NetMon: A GPU-accelerated Network Performance Monitoring System for Large Scale Scientific Collaborations

At Fermilab, we have prototyped a GPU-accelerated network performance monitoring system, called G-NetMon, to support large-scale scientific collaborations. Our system exploits the data parallelism that exists within network flow data to provide fast analysis of bulk data movement between Fermilab and collaboration sites. Experiments demonstrate that our G-NetMon can rapidly detect sub-optimal bulk data movements.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2011

G-NetMon: a GPU-accelerated network performance monitoring system

At Fermilab, we have prototyped a GPU-accelerated network performance monitoring system, called G-NetMon, to support large-scale scientific collaborations. In this work, we explore new opportunities in network traffic monitoring and analysis with GPUs. Our system exploits the data parallelism that exists within network flow data to provide fast analysis of bulk data movement between Fermilab and collaboration sites. Experiments demonstrate that our G-NetMon can rapidly detect sub-optimal bulk data movements.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2010

An evaluation of parallel optimization for OpenSolaris Network Stack

Computing is now shifting towards multiprocessing. The fundamental goal of multiprocessing is improved performance through the introduction of additional hardware threads or cores (referred to as 'cores' for simplicity). Modern network stacks can exploit parallel cores to allow either message-based parallelism or connection-based parallelism as a means to enhance performance. OpenSolaris has redesigned and parallelized to better utilize additional cores. Three special technologies, named Softring Set, Soft ring and Squeue are introduced in OpenSolaris for stack parallelization. In this paper, we study the OpenSolaris packet receiving process and its core parallelism optimization techniques. Experiment results show that these techniques allow OpenSolaris to achieve better network I/O performance in multiprocessing environments; however, network stack parallelization has also brought extra overheads for system. An effective and efficient network I/O optimization in multiprocessing environments is required to cross all levers of the network stack from network interface to application.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2010

Why Does Flow Director Cause Packet Reordering?

Intel Ethernet Flow Director is an advanced network interface card (NIC) technology. It provides the benefits of parallel receive processing in multiprocessing environments and can automatically steer incoming network data to the same core on which its application process resides. However, our analysis and experiments show that Flow Director cannot guarantee in-order packet delivery in multiprocessing environments. Packet reordering causes various negative impacts. E.g., TCP performs poorly with severe packet reordering. In this paper, we use a simplified model to analyze why Flow Director can cause packet reordering. Our experiments verify our analysis.

Wu, Wenji↗

DOE OSTI2010

A Transport-Friendly NIC for Multicore-Multiprocessor Systems

Receive side scaling (RSS) is a network interface card (NIC) technology. It provides the benefits of parallel receive processing in multiprocessing environments. However, existing RSS-enabled NICs lack a critical data steering mechanism that would automatically steer incoming network data to the same core on which its application process resides. This absence causes inefficient cache usage if an application is not running on the core on which RSS has scheduled the received traffic to be processed. In Linux systems, it cannot even ensure that packets in a TCP flow are processed by a single core, even if the interrupts for the flow are pinned to a specific core. This results in degraded performance. In this paper, we develop such a data steering mechanism in the NIC for multicore or multiprocessor systems. This data steering mechanism is mainly targeted at TCP, but it can be extended to other transport layer protocols. We term a NIC with such a data steering mechanism 'A Transport Friendly NIC' (A-TFN). Experimental results have proven the effectiveness of A-TFN in accelerating TCP/IP performance.

Wu, Wenji↗