Dror Goldenberg

Hadoop acceleration through network levitated merge

Hadoop is a popular open-source implementation of the MapReduce programming model for cloud computing. However, it faces a number of issues to achieve the best performance from the underlying system. These include a serialization barrier that delays the reduce phase, repetitive merges and disk access, and lack of capability to leverage latest high speed interconnects. We describe Hadoop-A, an acceleration framework that optimizes Hadoop with plugin components implemented in C++ for fast data movement, overcoming its existing limitations. A novel network-levitated merge algorithm is introduced to merge data without repetition and disk access. In addition, a full pipeline is designed to overlap the shuffle, merge and reduce phases. Our experimental results show that Hadoop-A doubles the data processing throughput of Hadoop, and reduces CPU utilization by more than 36%.

Zero copy sockets direct protocol over infiniband-preliminary implementation and performance analysis

Sockets direct protocol (SDP) is a byte-stream transport protocol implementing the TCP SOCK/spl I.bar/STREAM semantics utilizing transport offloading capabilities of the infiniband fabric: Under the hood, SDP supports zero-copy (ZCopy) operation mode, using the infiniband RDMA capability to transfer data directly between application buffers. Alternatively, in buffer copy (BCopy) mode, data is copied to and from transport buffers. In the initial open-source SDP implementation, ZCopy mode was restricted to asynchronous I/O operations. We added a prototype ZCopy support for send()/recv() synchronous socket calls. This paper presents the major architectural aspects of the SDP protocol, the ZCopy implementation, and a preliminary performance evaluation. We show substantial benefits of ZCopy when multiple connections are running in parallel on the same host. For example, when 8 connections are simultaneously active, enabling ZCopy yields a bandwidth growth from 500 MB/s to 700 MB/s, while CPU utilization decreases 8 times.

Transparently Achieving Superior Socket Performance Using Zero Copy Socket Direct Protocol over 20Gb/s InfiniBand Links

Sockets Direct Protocol (SDP) is a byte stream protocol that utilizes the capabilities of the InfiniBand fabric to transparently achieve performance gains for existing socket-based networked applications. In this paper we discuss an implementation of Zero Copy support for synchronous send()/recv() socket calls, that uses the remote DMA capability of InfiniBand for SDP data transfers. We added this support to the open-source implementation of SDP over InfiniBand. We evaluate this implementation over a 20 Gb/s InfiniBand link. We demonstrate scalability of Zero Copy and show its benefits for systems that utilize multiple socket connections in parallel. For example, enabling Zero Copy with 8 active connections yields a bandwidth growth from 630MB/s to 1360MB/s, at the same time reducing the CPU utilization by a factor often

Architecture and Implementation of Sockets Direct Protocol in Windows

Sockets direct protocol (SDP) is a byte stream protocol that utilizes the capabilities of the InfiniBand fabric to transparently achieve performance gains for existing socket-based networked applications. We implemented SDP stack for the Windows operating system that is fully interoperable with Linux. The paper describes the early experience with the implementation of the protocol stack. We go through the motivation, the main implementation architectural aspects and challenges. We present preliminary performance results. Running over 20Gb/s InfiniBand double data rate (DDR) links we observed bandwidth record of 1316MB/S

Development and Extension of Atomic Memory Operations in OpenSHMEM

A distinguishing characteristic of OpenSHMEM compared to other PGAS programming model implementations is its support for atomic memory operations (AMOs). It provides a rich set of AMO interfaces supporting 32-bit and 64-bit datatypes. On most modern networks, network-implemented AMOs are known to outperform software-implemented AMOs. So, for achieving high-performance, an OpenSHMEM implementation should try to offload AMOs to the underlying network hardware when possible. Nevertheless, the challenge arises when (a) underlying hardware does not support full set of atomic operations, (b) more that one device is used, and (c) heterogeneous systems with multiple types of devices are involved. In this paper, we analyze the challenges and discuss potential solutions to address these challenges.