CSC/ECE 506 Fall 2007/wiki1 10 mt: Difference between revisions

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Since 1999, little advancement has been made in the field of dataflow architecture. Dataflow was primarily abandoned due to several problems. The dynamic dataflow model requires some sort of associative memory in order to store the tokens waiting  to be matched. Unfortunately, even in moderate size programs this tends to be the required memory tends to be large and therefore not very cost efficient.
Since 1999, little advancement has been made in the field of dataflow architecture. Dataflow was primarily abandoned due to several problems.  
#The dynamic dataflow model requires some sort of '''associative memory''' in order to store the tokens waiting  to be matched. Unfortunately, even in moderate size programs this tends to be the required memory tends to be large and therefore not very cost efficient.
#Dataflow programs typically made use of multiple threads since parallel functions and loops were frequently used. Therefore, if there wasn't enough of a workload for multiple threads, '''single threaded execution''' of a program provided poor performance.

Revision as of 16:17, 3 September 2007


Dataflow & Systolic Architectures

Dataflow and systolic are two of the many possible parallel computer architectures. Unlike shared address, message passing and data parallel processing, the dataflow and systolic architectures were not as commonly used for parallel programming systems although they recieved a considerable amount of analysis from both private industry and academia.

Dataflow

Dataflow architecture is in oppostion to the von Neumann or control flow architecture which has memory, and I/O subsystem, an arithmetic unit and a control unit. The one shared memory is used for both program instructions and data with a data bus and address bus between the memory and processing unit. Because instructions and data must be fetched in sequential order, a bottleneck may occur limiting the throughput between the CPU and the memory.

The dataflow model of architecture, in contrast, is a distributive model where there is no single point of control and the execution of an instructions takes place only when the required data is available. Dataflow models are typically represented as a graph of nodes where each node in the graph is an operation to be executed when its operands become available along with the address of the subsequent nodes in the graph that need the results of the operation.

Included in the dataflow model of architecture there is also static and dynamic dataflow. The static dataflow model is characterized by the use of the memory address to specify the destination nodes that are data dependent. The dynamic model uses content-addressable memory which searches the computer memory for specific tags. Each subprogram or subgraph should be able to execute in parallel as separate instances. In the dynamic dataflow model, programs are executed by dealing with tokens which contain both data and a tag. A node is executed when incoming tokens with identical tags are present.

Systolic

New Developments in Dataflow and Systolic Architectures

Since 1999, little advancement has been made in the field of dataflow architecture. Dataflow was primarily abandoned due to several problems.

  1. The dynamic dataflow model requires some sort of associative memory in order to store the tokens waiting to be matched. Unfortunately, even in moderate size programs this tends to be the required memory tends to be large and therefore not very cost efficient.
  2. Dataflow programs typically made use of multiple threads since parallel functions and loops were frequently used. Therefore, if there wasn't enough of a workload for multiple threads, single threaded execution of a program provided poor performance.