The POPCORN Project -- An Interim Report

Distributed Computation over the Internet in Java

Noam Camiel, Shmulik London, Noam Nisan, Ori Regev
{demian,londons,noam,regev}@cs.huji.ac.il
Institute of Computer Science, Hebrew University
Jerusalem, Israel

Abstract

The POPCORN system [1], under development in the Hebrew University of Jerusalem, is aimed at providing a global, Internet-wide, distributed virtual computer. In principal, all the millions of processors connected to the Internet at any given moment can serve as part of a single huge parallel virtual machine. Towards this goal we provide an infrastructure for programming distributed computations in Java using our libraries, and executed using all processors on the Internet which care to participate. Market incentives for such participation are also supported by the system.

Introduction

There are currently millions of processors connected to the Internet. At any given moment, many if not most of them are idle. An obvious and appealing idea is to utilize these computers for running applications which require large computational power. This would allow what may be termed "global computing" -- a single computation carried out by cooperation between processors global-wide.

In the context of a single local network, this idea has been successfully attempted by rather many systems by now, especially due to the influence of the work done in "Network of Workstations" (NoW)[2]. However, the situation is more complicated when it comes to the whole Internet. Several technical difficulties immediately come to mind: the operating systems of remote computers can not be changed, as is often done in NoWs; code must be dynamically transferred to remote machines with unknown hardware and software; the remote machines should be secured from malicious code, etc.

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Any general framework for global computation would thus require mechanisms for "mobile-code" providing code mobility as well as security over the Internet. Indeed, until recently such general global systems were not feasible, and only special-purpose computations have been done globally [3]. The recent wide availability of the Java language [4] with its virtual machine embedded in popular browsers and its security mechanisms finally allows such "global" systems to be built. The POPCORN system is built on top of Java, and thus allows cooperation of all Java-enabled computers on the Internet -- in a safe and simple manner (and totally in user-space). We know of several other on-going projects which utilize Java towards similar goals [6,7,8].

Even after the basic code mobility and safety problems are resolved, there are still some very fundamental differences between global computing systems (such as those POPCORN aims at) and local distributed systems (such as NoWs). The first difference is a matter of scale: The Internet is much more "distributed": The communication bandwidth is smaller, the latency higher, the reliability lower. Processors come and go with no warning and no way to control them. On the positive side, the potential number of processors is huge. We believe that while the Internet currently cannot hope to serve as a totally general purpose efficient parallel computer, it can still provide excellent computational resources for a wide variety of computational problems. In particular, we feel that many optimization problems and techniques (e.g. brute-force search, hill climbing, simulated annealing, genetic algorithms, branch-and-bound, etc.) can be efficiently implemented over the Internet.

A more interesting difference is due to the distributed ownership of the processors on the Internet. Since each processor is owned and operated by a different person or organization, there is no a-priori motivation for cooperation (why should my computer work on your problem?). Clearly a motivation for cooperation must be provided by a global computing system. In addition processors on the Internet may be malicious or faulty, and thus can not necessarily be trusted.

POPCORN Overview

POPCORN's basic function is to provide any programmer on the Internet with a simple virtual parallel computer. This virtual machine is implemented by utilizing all Java-enabled processors on the Internet which care to participate at any given moment. In order to motivate this participation, a market-based payment mechanism for CPU-time underlines the whole system.

There are three distinct entities in the POPCORN system:

  1. The parallel program written (in Java) using the POPCORN API. This program acts as a "CPU-time buyer".
  2. The "CPU-time seller" which allows its CPU to be used by other parallel programs. This is done simply by visiting a web-site using a Java-enabled browser.
  3. The "market" which serves as a meeting place for buyers and sellers of CPU-time.

Writing Parallel POPCORN Programs

We provide an API (in Java) to be used for writing parallel POPCORN programs. The rational for providing this API instead of relying on Java's own mechanisms is that we do not believe that general parallelism can be efficiently supported over the Internet. Our API provides what we feel can be efficiently provided. The API resembles the usage of remote method invocation (RMI [5]) (an object oriented variant of Remote Procedure Call) which we call a computelet.

A POPCORN computation is normally composed of a single thread of execution running on the local machine. This thread may send off well defined sub-computations for remote execution. A computelet abstracts this sub-computation, including the code to be executed as well as the data needed. Each invoked computelet is synchronously executed remotely, and the local thread of computation is informed when the answer arrives. There is a semantic difference between computelets and usual RMI: the invoking program does not care or specify where the computelet actually gets executed, while the remote machine may execute any computelet since its code originates from the caller.

While this notion of computelets is weaker than general shared-memory or message passing parallel programming notions, we believe that it fits well global computation. The main advantage is that by encapsulating a well defined part of the parallel program as a computelet, we have great control over its usage, price, resource use, etc. We can verify its results, re-send it if needed, pay for it, etc. In global computation where parts of the computation may get lost, be incorrect, require payment, etc., this well-defined control becomes important.

"Selling" your CPU time

A basic design decision of POPCORN is that "selling" CPU time should be simple. In order to allow your CPU to be used for other people's computations, it suffices for you to visit a web-site (the market) using any Java-enabled browser. This web-site includes a Java applet, which loads and executes the needed code. All this, transparently to the "seller" (except for a clear notification that this is taking place). At this web-site the seller may also choose how he gets "paid" for this service.

The Market

The "market" serves as a meeting place for buyers and sellers of CPU-time. Parallel programs (buyers) visit it in order to buy CPU time, and any computer may visit it in order to sell its CPU-time. A micro-economy of CPU-time is thus created, which the market manages. The market has several other functions as well: it serves as a trusted party, it is responsible for actually distributing current computations between all on-line sellers, it decides on priorities, load balancing, etc.

The Current Implementation (March '97)

We have implemented and tested a basic but complete system. This system is reachable from the POPCORN home page [1], either for selling CPU-time or for buying CPU-time for your own global programs. In order to write your own POPCORN-based global program, the POPCORN packages must be downloaded from our site; we also provide a "tutorial for developers" there. In this section we briefly describe the features provided by the current implementation.

Payments for CPU-time

The POPCORN system currently uses a pseudo-currency termed a "popcoin". (In a "real implementation" this could just be real money). All popcoin accounts are handled by the market: your popcoin balance increases when you sell CPU-time and decreases when you buy it. In order to buy CPU-time, i.e. run a parallel POPCORN program, you need to have enough popcoins in your account to pay for it.

Selling CPU-time is extremely easy: you visit the web-page of our market with a Java-1.1-enabled browser (we use the Java 1.1 serialization package in our implementation hence the need for Java 1.1). A seller may quit the computation at any given moment by leaving the web-page, losing the current executing computelet, but keeping all earnings for previous computelets. At this web-page the seller can choose between two options for getting paid. The first possibility is to play one of the simple games we provide, with the knowledge that while the game is being played the CPU will also be used in the background for executing computelets. This possibility does not add popcoins to the seller's account as his payment is the game itself.

The second possibility a seller has is to get paid in popcoins. For this possibility, the seller enters the popcoin-account ID to which the popcoins should be deposited. The market guarantees that the highest paying available computelet will be sent to the current sellers at any given moment -- thus maximizing the sellers' profits. The popcoins earned this way have no value outside of the POPCORN system, but may later be used inside the POPCORN system for buying CPU-time in future parallel programs. In addition, popcoins can be used for "buying" some (silly) information we provide or for playing some simple games we provide.

A buyer of CPU-time must have previously established an account in the market. As long as he keeps a positive popcoin balance, new computelets may be sent for remote execution. Each computelet is sent to the market with a price-tag set by the buyer. This price-tag may be in one of two forms. In the first form the buyer declares how many popcoins he is willing to offer for the execution of the whole computelet. When the computelet's answer is sent to him this amount is deducted from his popcoin account. In the second variant the buyer declares how many popcoins he is willing to offer for each unit of computation in the computelet. The amount of units of computation actually taken by the computelet is transparently approximated by POPCORN using a simple benchmark which it runs in the background on the sellers' processor while the computelet runs.

The only motivation for offering a high price for a computelet is that higher paying computelets get priority over lower paying ones. Thus if your offer is too low, your computelet may never get executed since more recent yet higher paying computelets may take up all available CPU-time. To allow the buyer more control over the price, we supply a mechanism by which the buyer may instruct the market to automatically increase the price at a given rate until sellers can be found.



Figure 1: The Popcorn Seller and Market Monitoring page

The POPCORN API

The basic notion in a POPCORN program is the Computation Packet. A Computation Packet is a basic unit of computation for remote execution. The heart of the computation packet is the computelet. The comptelet is what actually gets transmitted over the Internet to the seller and includes both the code to be executed as well as the data this code operates on. The computation packet encapsulates in addition all information regarding the processing of this computelet: the price offered for it, how it is handled locally when the answer arrives, how it is verified, what if the remote computation fails somehow, etc. The main POPCORN program is basically responsible for creating computation packets and then handling the results when they arrive -- this may result in further computation packets.

Technically, in the simplest form, a POPCORN programmer is expected to subclass the two basic classes: popcorn.ComputationPacket and popcorn.Computelet. In the Computelet subclass he overrides the Computelet.compute() method with the code to be executed remotely. In the ComputationPacket subclass he overrides the ComputationPacket.completed() method with the code which handles the results when they arrive. In addition a main program is written which generates the computation packets needed for the whole computation. Below we list an example of a complete POPCORN program which finds the maximum of a function using simple brute force search of all possibilities. Notice that no verification of the remote computations is attempted in this program, yet incorrect results do not completely destroy the computation but rather can only result in suboptimality of the solution.

import popcorn.*;

public class FindMaxPacket extends ComputationPacket {
    static int maxarg;

    public static void main(String[] args) {
        maxarg=0;
        for (int a=0; a < 10000; a+=100)
            new FindMaxPacket(a,a+99).go();
        collectAll();
        System.out.println("maxarg(g(x))="+maxarg);
    }

    public FindMaxPacket(int from, int till) {
        super(FindMaxComputelet(from,till));
	this.setContract(new StandardBuyerContract(
			 new FixedPopcoinPacketBid(10.0));
    }

    public void completed() {
        update((Integer)result().intValue());
    }

    static synchronized void update(int candidate) {
        maxarg = (FindMaxComputelet.g(candidate) >
                          FindMaxComputelet.g(maxarg)) ? 
                          candidate : maxarg;
    }
}

class FindMaxComputelet implements Computelet {
    private int from,till;

    public FindMaxComputelet(int from, int till){
        this.from=from; 
        this.till=till;
    }
    
    public Object compute() {
        int maxarg=from;
        for (int x=from; x<=till; x++) 
            maxarg = (g(x)>g(maxarg)) ? x : maxarg;
        return new Integer(maxarg);
    }
 
    // the function we want to maximize
    public static int g(int x) {
        return . . .
    }
}

Further Research

We view the POPCORN system as an infrastructure and test-bed for many questions and ideas that naturally arise. Indeed, we have left numerous "hooks" and interfaces in the current POPCORN implementation which are aimed at allowing modifications and experimentation. Some of the main areas which we are working on are sketched below.

Algorithms

The type of computations which seem to fit the POPCORN system (or any "global" computation system) will have two characteristics: (1) they are rather loosely coupled (2) They can be made resilient to failures of computelets. It is a challenge to identify the problems which are amenable to such algorithms, and to design them.

Computelet answer verification

The computelet results received from the sellers should in principal be verified, since a malicious seller may return fake results instead of running the computelet. Many possibilities for this verification exist:
  1. Send each computelet several times to different sellers and compare the results.
  2. If the penalty for cheating is high enough, then spot-checks should suffice.
  3. Design the computelets to return an easily checked NP-type proof of correctness.
  4. Various program-testing and checking techniques [9] could be employed.
  5. A sub-problem with a known answer can be hidden inside each computelet.
Finally, we believe that algorithms for many problems may be designed so as to be resistant to such cheating in computelet results.

Payments

Obviously there are many possible payment types which may be employed:
  1. Money.
  2. CPU-time credits.
  3. Information.
  4. Lottery systems.
  5. Volunteering for good causes.
  6. Inside a company, "brownie points" will suffice.
All these types of payments may be per computelet or per unit of computation. In addition, many constraints may be specified, e.g. a deadline for the answer.

Economic policies

Perhaps the most interesting and wide-open area of research is understanding the types of behavior we get in such programmed trading between large numbers of buyers and sellers. Various economic strategies for the buyers, the sellers, and the markets should be defined. This should be done both from the "global" perspective (define globally-good market rules), and from each participant's point of view. It seems that a new research area dealing with such types of questions is now emerging which sometimes is called "dynamics of computation", "emergent behavior", "economic agents", and other names.

Payment delivery

In our current system the market is responsible for keeping and managing the popcoin-accounts of all participants. Clearly, in a real system payments should be delivered using some electronic-payment scheme. Many of the current micro-payment schemes seem to fit this well.

Scalability

The simple three-tier implementation described above is clearly not scaleable. However, the system architecture is totally scaleable in two ways. First, many markets can be deployed. These can be organized either as a single economic unit, balancing the load between them and thus avoiding a single hot-spot. Many economically competing markets may be deployed, perhaps trading with each other, allowing buyers and sellers choice of markets. The second way salability can be obtained is by allowing computlets to further spawn multiple computelets, creating an arbitrary computation tree.

Other traded goods

CPU-time is only one good which may be traded over the Internet. In fact, it may be argued that it is perhaps the cheapest such good. Other goods which may be bought and sold by computer programs using a mechanism similar to POPCORN include:
  1. Disk space
  2. Information
  3. Communication bandwidth
  4. Algorithms for specific tasks
  5. Human advice

References

[1] The POPCORN home page. http://www.cs.huji.ac.il/labs/popcorn.

[2] Network of Workstations. Patterson et al. http://now.cs.berkeley.edu

[3] Factoring by Web. Lenstra. http://www.npac.syr.edu/factoring/info.html

[4] JavaSoft home page. http://www.javasoft.com

[5] RMI http://chatsubo.javasoft.com/current/index.html

[6] ParaWeb: Towards World-wide Supercomputing http://villi.cs.yorku.ca/reports/paraweb/Welcome.html

[7] SuperWeb: Towards a Global Web-Based Parallel Computing Infrastructure / Albert D. Alexandrov, Maximilian Ibel, Klaus E. Schauser, Chris J. Scheiman. Manuscript.

[8] A. Baratloo, M. Karaul, Z. Kedem, and P. Wyckoff. Charlotte: Metacomputing on the Web. In Proceedings of 9th Conference on Parallel and Distributed Computing System, 1996.

[9] Blum M., Luby M., Rubinfeld R., "Self-Testing/Correcting with Application to Numerical Problems", STOC 1990.



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