Widening the Remote Visualization Bottleneck

Widening the Remote Visualization Bottleneck Simon Stegmaier Joachim Diepstraten Manfred Weiler Thomas Ertl Visualization and Interactive Systems Group, University of Stuttgart Universitatsstraße¨ 38, D-70569 Stuttgart∗ Abstract time the simulation parameters have changed. This may be a great advantage, given that many wide-area network With the advent of generic remote visualization solu- connections are still very slow compared to LANs. Sec- tions, accessing distant graphics resources from the desk- ond, replicating the datasets on the hosts of every researcher top is no longer restricted to specially tailored applica- working with the data multiplies the overall memory and tions. However, current solutions still suffer from poor in- disk requirements and unnecessarily raises the costs for teractivity due to limited network bandwidth and high la- desktop computers. Third, raw simulation data is often con- tency. In this paper we present several improvements to fidential and a transfer via insecure network connections our remote visualization system in order to overcome these may be unacceptable. drawbacks. Different image compression schemes are eval- To overcome these drawbacks of decentralized data stor- uated with regard to applicability for scientific visualiza- age, the concept of remote visualization was introduced. tion, showing that image compression alone cannot guar- The basic idea is simple: The datasets are visualized on the antee interactive frame rates. Therefore, we furthermore high-performance computer–the server–and only the ren- present different techniques for alleviating the bandwidth dered images are transmitted to the researcher. This min- limit, including quality reduction during user interaction or imizes the resources required at the client. However, albeit animations. Latency aspects are addressed by employing compression techniques can be employed to reduce the size multi-threading for asynchronous compression and utiliz- of the images to be transmitted, the data rates necessary for ing features of modern programmable graphics adapters for interactive frame rates usually restrict the applicability of performing the image compression entirely on the graphics remote visualization solutions to high-speed networks, usu- card. The presented ideas are integrated in our remote vi- ally LANs. sualization system without violating universality. In this paper, several methods for achieving interactive frame rates even in low-bandwidth environments are discussed and evaluated using our own generic remote visu- 1. Introduction alization solution as a testing platform. The paper is orga- nized as follows: Related work is discussed in Section 2. Many scientific simulations calculated these days pro- Our remote visualization solution is described in Section 3, duce datasets of sizes that cannot be handled with PCs or including a revised architecture required for incorporating workstations typically available at the desks of the analyz- the optimizations. Software-based optimization methods ing researchers. However, speaking in Richard Hamming’s are discussed in Section 4, followed by the presentation of words, the purpose of computing is insight, not numbers; a hardware-based image compression in Section 5. Recom- thus, if analyzing the data becomes increasingly difficult, mendations and a conclusion are given in Section 6. the value of the simulation decreases. A highly effective way to analyze datasets is scientific 2. Related Work visualization. However, scientific visualization not only requires a fast CPU and huge amounts of memory (both main Engel et al. [3] developed a framework for providing re- memory and secondary storage) but also high rendering mote control to OpenInventor and Cosmo3D applications. performance provided by modern graphics adapters. Ob- The system transmits compressed images from the server viously, these resources are not always available and it is to a Java-based client and returns events generated at client impossible—especially for publicly-funded research insti- side via CORBA requests. The system requires substantial tutions like universities—to replace the computing equip- modifications of the visualization application and shows a ment each time the dataset sizes double. And even if this very low overall performance. was possible a central solution might still be favorable. Ma and Camp [8] developed a solution for remote visu- First, if the datasets remain on the host where they were alization of time-varying data over wide area networks. It generated, there is no need for transferring the data each involves a dedicated display daemon and a custom transport ∗[email protected] method which enables them to employ arbitrary compression techniques. Again, the presented system is not generic but targeted at a parallel volume rendering application. Bethel [1] presented Visapult, a system that combines minimized data transfers and workstation-accelerated rendering. Like the solutions developed by Engel, Ma, and Camp, Visapult requires modifications of the application in order to make it “network aware”. As another drawback, the system relies to some extent on the existence of hardware graphics acceleration on the local display. A truly generic solution was first described in detail by Stegmaier et al. [15]. The system takes advantage of the transport mechanisms part of the X Window System [10] leading to an extremely compact implementation and (in combination with VNC [12]) support for a very large va- riety of platforms for the client. Due to the abandonment of a proprietary data channel, no custom compression of images is supported. Wide-spread use of generic solutions came with the ad- Figure 1. GLX architecture as of Kilgard [6]. vent of SGI’s commercial OpenGL Vizserver [14]. OpenGL Vizserver allows a wide range of clients to access the ren- tionality is provided in two formats: as static libraries and dering capabilities of remote graphics servers. However, as shared libraries. It is up to the programmer to select a due to certain design decisions, the servers are restricted to suitable format. SGI workstations. Amongst other compression algorithms, For shared libraries only a link to the actual functionality Vizserver includes an implementation of Color Cell Com- is included in the application’s executable. Thus, dynami- pression [2]. cally linked applications allow the replacement of library functionality without relinking. Therefore, shared objects 3. Status Quo are the only suitable choice for library functionality that is not portable between different target platforms, e.g. the The remote visualization system presented in this work is GPU-dependent OpenGL libraries. based on the system described in [15]. The core idea can be Most systems that support load-time linking also support easily recognized by considering the way an OpenGL-based a second mechanism sometimes referred to as preloading. application generates images when the display is redirected Preloading allows to manipulate the stack that is used to to a remote host1 (left side of Fig. 1). All OpenGL com- resolve function references in dynamically linked applica- mands are encoded using the GLX protocol and transmitted tions, usually by setting an environment variable to an ob- to the remote host as part of the well-known X11 proto- ject file that redefines the functions to be overridden. There- col stream. The stream is then decoded by the receiving X fore, preloading presents an easy method for non-invasively server and the OpenGL commands are executed exploiting customizing library behavior. However, completely redefin- the resources available at the destination host. This is ex- ing library functions is not trivial—in particular if the func- actly what is not desired for hardware-accelerated remote tions perform complex tasks. visualization since we cannot benefit from the graphics re- To cope with this problem, many systems also support sources of the host running the application. Thus, the trans- run-time linking. With run-time linking, symbol resolution mission of OpenGL commands must be suppressed (to ob- is performed after the program has started instead of dur- tain the scenario on the right side of Fig. 1) and only the ing the loading phase. The original functionality can then rendered images should be transferred to the host where the be recovered by opening the original shared object (usually user interaction occurs. In the remainder of this paper, we with dlopen) and determining the address of the relevant will use the terms render server and interaction server to function from its name (with dlsym). refer to the two hosts involved in the visualization process. Surprisingly, the required modifications of the GLX ar- 3.2 Library Architecture chitecture can be obtained through a single shared object linked to the visualization application at program start-up. Using the described dynamic linking functionality, a generic remote visualization solution can be obtained by 3.1 Dynamic Linking preloading library functions from two groups. • XOpenDisplay Almost all applications developed these days make use Set-up functions like , glXChooseVisual glXMakeCurrent of functionality provided as libraries. Usually, library func- , and • 1We will only address remote visualization systems based on the X Trigger functions like glXSwapBuffers, Window system in this paper. glFlush, and glFinish The set-up functions make sure that the stream of OpenGL commands is directed

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