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Tony Chen, Sunjeev Sikand, and John Kerwin CSE 291 - Programming Sensor Networks May 23, 2003 PowerPoint Presentation
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Overview of An Efficient Implementation Scheme of Concurrent Object-Oriented Languages on Stock Multicomputers. Tony Chen, Sunjeev Sikand, and John Kerwin CSE 291 - Programming Sensor Networks May 23, 2003 Paper by: Kenjiro Taura, Satoshi Matsuoka, and Akinori Yonezawa. Background.

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Overview of An Efficient Implementation Scheme of Concurrent Object-Oriented Languages on Stock Multicomputers

Tony Chen, Sunjeev Sikand, and John Kerwin

CSE 291 - Programming Sensor Networks

May 23, 2003

Paper by: Kenjiro Taura, Satoshi Matsuoka, and Akinori Yonezawa

background
Background
  • Most of the work done on high performance, concurrent object-oriented programming languages (OOPLs) has focused on combinations of elaborate hardware and highly-tuned, specially tailored software.
  • These software architectures (the compiler and the runtime system) exploit special features provided by the hardware in order to achieve:
    • Efficient intra-node multithreading
    • Efficient message passing between objects
special hardware features
Special Hardware Features
  • The hardware manages the thread scheduling queue, and automatically dispatches the next runnable thread upon termination of the current thread.
  • Processors and the network are tightly connected.
    • Processors can send a packet to the network within a few machine cycles.
    • Dispatching a task upon packet arrival takes only a few cycles.
objective of this paper
Objective of this Paper
  • Demonstrate software techniques that can be used to achieve comparable intra-node multithreading, and inter-node message passing performance on conventional multicomputers, without special hardware scheduling and message passing facilities.
system used to demonstrate these techniques
System Used to Demonstrate these Techniques
  • The authors developed a runtime environment for a concurrent object- oriented programming language called ABCL/onAP1000.
  • Used Fujitsu Laboratory’s experimental multicomputer called AP1000.
    • 512 SPARC chips running at 25 MHz
    • Interconnected with a 25 MB/s torus network
computation programming model
Computation/Programming Model
  • Computation is carried out by message transmissions among concurrent objects.
    • Units of concurrency that become active when they accept messages.
  • Multiple message transmissions may take place in parallel, so objects may become active simultaneously.
  • When an object receives a message, the message is placed in its message queue, so that messages can be invoked one at a time.
computation programming model cont
Computation/Programming Model (cont.)
  • Messages can contain mail addresses of concurrent objects in addition to basic values such as numbers and booleans.
  • Each object has its own autonomous single thread of control, and its own encapsulated state variables.
  • Objects can be in dormant mode if they have no messages to process, active mode if they are executing a method, or waiting mode if they are waiting to receive a certain set of messages.
possible actions within a method
Possible Actions Within a Method
  • Message Sends to other concurrent objects
    • Past type – sender does not wait for a reply message
    • Now type – sender waits for a reply message
      • Reply messages are sent through a third object called a reply destination object, which resumes the original sender upon the reception of the reply message.
  • Creation of concurrent objects
possible actions within a method cont
Possible Actions Within a Method (cont.)
  • Referencing and Updating the contents of state variables
  • Waiting for a specified set of messages
  • Standard Operations (like arithmetic operations) on values stored in state variables
scheduling process
Scheduling Process
  • Scheduling for sequential OOPLs simply involves a method lookup and a stack-based function call.
  • For concurrent OOPLs, scheduling of methods is not necessarily LIFO-based, since methods may be blocked to wait for messages, and resumed upon the arrival of a message.
    • Therefore, a naïve implementation must allocate invocation frames from the heap instead of the stack, and use a scheduling queue to keep track of pending methods.
scheduling process cont
Scheduling Process (cont.)
  • In addition, since it may not be possible for a receiver object to immediately process incoming messages, each object must have its own message queue to buffer incoming messages.
  • This can lead to substantial overhead for frame allocation/deallocation, and queue manipulation, for both the scheduling and message queues.
example of a na ve scheduling mechanism
Example of a Naïve Scheduling Mechanism
  • A naïve implementation of message reception / method invocation for an object would require:
    • Allocation of an invocation frame to hold local variables and message arguments of the method.
    • Buffering a message into the frame.
    • Enqueueing the frame into the object message queue.
    • Enqueueing the object into the scheduling queue (if it is not already there).
key observation for intra node scheduling strategy
Key Observation for Intra-node Scheduling Strategy
  • In many cases, this full scheduling mechanism is not necessary, and we can use more efficient stack-based scheduling.
  • If an object is dormant, meaning it has no messages to be processed, its method can be invoked immediately upon message reception, without message buffering or schedule queue manipulation.
  • If it is active, then the message is buffered, and the method is invoked later via the scheduling queue.
scheduling strategy implementation
Scheduling Strategy Implementation
  • We need a mechanism to implement this strategy efficiently.
  • We cannot perform a runtime check on every intra-node message send to determine whether or not the receiver is dormant.
  • When a running object becomes blocked on the stack, we must be able to resume other objects.
virtual function tables
Virtual Function Tables
  • A Virtual Function Table Pointer (VFTP) points to a Virtual Function Table, which contains the address of each compiled function (method) of the class.
key idea in object representation
Key Idea in Object Representation
  • Each class has multiple virtual function tables, each of which roughly corresponds to a mode (dormant, active, and waiting) of an object.
  • When an object is in dormant mode, its Virtual Function Table Pointer (VFTP) points to the table that contains the method bodies.
  • When an object is active, the VFTP points to a virtual function table that holds tiny queueing procedures, which simply allocate a frame, store the message into the frame, and enqueue it on the object’s message queue.
benefits of multiple virtual function tables
Benefits of Multiple Virtual Function Tables
  • With multiple virtual function tables, a sender object does not have to do a runtime check of whether or not the receiver object is dormant.
  • Instead this check is built into the virtual function table look-up, which is already a necessary cost in object-oriented programming languages.
benefits of multiple virtual function tables cont
Benefits of Multiple Virtual Function Tables (cont.)
  • Can be used to implement selective message reception where acceptable messages trigger functions that restore the context of the object, and unacceptable messages trigger queueing procedures.
  • Can also be used to initialize an object’s state variables, by creating a table that points to initialization functions that initialize variables before calling a method body.
combining the stack with the scheduling queue
Combining the Stack with the Scheduling Queue
  • When a method is invoked on a dormant object, an activation frame is allocated on the stack, thereby achieving fast frame allocation/deallocation.
  • If this invocation blocks in the middle of a thread, it allocates another frame on the heap, and saves its context to this frame, which will survive until termination of the method.
  • The scheduling queue is used to schedule preempted objects that saved their context into a heap-allocated frame, or to invoke messages that were buffered in a message queue.
inter node software architecture
Inter-node Software Architecture
  • Important for message passing between objects on different nodes, and object creation on a remote node.
  • Assumes the hardware (or message passing libraries) provides an interface to send and receive messages asynchronously.
  • Uses an Active Message-like mechanism, where each message attaches its own self-dispatching message handler, which is invoked immediately after the delivery of the message.
customized message handlers
Customized Message Handlers
  • Providing a customized message handler for each kind of remote message allows the system to achieve low overhead remote task dispatching.
  • Message handlers are classified into the following categories:
    • Normal message transmission between objects
    • Request for remote object creation
    • Reply to remote memory allocation request
    • Other services such as load balancing, garbage collection, etc.
remote object creation
Remote Object Creation
  • A mail address of an object is represented as <processor number, pointer>.
  • This provides maximum performance for local object access, and avoids the overhead of export table management.
  • Object creation on a remote node requires a memory allocation on the remote node to generate a remote mail address.
remote object creation cont
Remote Object Creation (cont.)
  • Since the latency of remote communication is unpredictable, and the cost of context switching is high, it is unacceptable to wait for the remote node to allocate memory and return a pointer.
  • Therefore the system uses a prefetch scheme, where each node manages predelivered stocks of addresses of memory chunks on remote nodes, and these addresses are used for remote object allocation.
  • A node only has to wait for a remote address to be allocated if its local stock is empty.
typical remote object creation sequence
Typical Remote Object Creation Sequence
  • The requester node obtains a unique mail address locally from the stock.
  • It sends a creation request message to the node specified by the mail address.
  • The target node performs class-specific initialization (such as initialization of the virtual function table) of the created object upon receipt of the creation message.
  • The target node allocates a replacement chunk of memory, and returns its address to the requester node.
  • The requester replenishes its stock upon receipt of the replacement address.
comparison of send reply latency
Comparison of Send/Reply Latency

Send and reply latency for the ABCL/onAP1000 conventional multicomputer is only about 4 times that of the ABCL/onEM4 fine-grain machine, and 2 times that of the CST fine-grain machine.

benchmark statistics
Benchmark Statistics
  • To evaluate these techniques on real applications, the authors measured the performance of the N-queen exhaustive search algorithm for N = 8 and N = 13.
  • They compared these results to the results of running the same programs on a single CPU SPARC station 1+, which uses the same CPU that is used in the AP1000.
the effect of stack based scheduling
The Effect of Stack-based Scheduling
  • To demonstrate the effect of stack-based scheduling, they compared the performance of the N-queen program using stack-based scheduling, to its performance using a naïve scheduling mechanism that always buffers a message in the message queue of the receiver object, and schedules the object through the scheduling queue.
  • In these programs, approximately 75% of local messages are sent to dormant objects.
  • In general, they observed a speedup of approximately 30%.
conclusions
Conclusions
  • The authors proposed a software architecture for concurrent OOPLs on conventional multicomputers that can compete with implementations on special-purpose, fine-grain architectures.
  • Their stack-based intra-node scheduling mechanism significantly reduces the average cost of intra-node method invocation.
  • Their Active Message-like messages, and address prefetch scheme minimize the cost of inter-node message passing, and remote object creation.
discussion
Discussion
  • The eternal question: How does this apply to sensor networks?
  • Low instruction count for intra-node scheduling
  • Power efficient remote object creation cuts down on communication
flaws
Flaws
  • Security problems related to active messages. User can run any code they desire.
  • Scalability for prefetching objects, if thousands of nodes results in lots of communication between nodes and memory becomes a scarce commodity.