Dataflow Processing. A.R. Hurson Computer Science Department Missouri Science & Technology

Transcription

1 A.R. Hurson Computer Science Department Missouri Science & Technology 1

2 Control Flow Computation Operands are accessed by their addresses. Shared memory cells are the means by which data is passed between instructions. Flow of control is implicitly sequential, but special control instructions can be introduced to explicitly identify concurrency. Fall

3 Control Flow Computation Program Counter(s) is (are) used to sequence the execution of instructions in a centralized environment. 3

4 A dataflow program is a program with a partial ordering defined by the data interdependencies. In a dataflow program the activation (execution) of an instruction is triggered (fired) by the availability of its input data. 4

5 a b a+b 5

6 Data Dependencies input (a,b,c) a := 2*a c := b 2-2*a*c b := -b/a c := sqrt(c) c := c/a b := b-c a := b+c output(a,b) 6

7 Dataflow Principles The dataflow model of computation deviates from the conventional control-flow method in two basic principles: asynchrony and functionality: 7

8 Dataflow Principles Asynchrony: an instruction is fired (executed) only when all the required operands are available. Functionality: any two enabled instructions can be executed in either order or concurrently i.e., no side-effects. 8

9 Dataflow Principles Within the scope of dataflow processing, implicit parallelism is achieved by allowing side-effect free expressions and functions to be evaluated in parallel. 9

10 Dataflow Principles In a dataflow environment, conventional concepts such as variables and memory updating are non-existent. Objects (operand values) are consumed by an actor (instruction) yielding a result object which is passed to the next actor(s). 10

11 Dataflow Principles Within the scope of a concurrent environment, dataflow computation addresses the programmability, memory latency, and synchronization issues. 11

12 Questions Define; programmability, memory latency, and synchronization. How have these issues been addressed in the conventional multiprocessor systems? Why does the dataflow model of computation offer good solutions for these problems? 12

13 Classification The dataflow model of computation has been traditionally classified as either static or dynamic: 13

14 In the static organization, a dataflow actor can be executed only when all of the tokens are available on its input arcs and no token exists on any of its output arcs. In the dynamic organization, a dataflow actor can be enabled only when all of the tokens of the same tag (color) are available on its input arcs. 14

15 Dataflow Graph A dataflow program can be represented as a directed graph, G = G(N,A), where nodes (actors) in N represent instructions, and arcs in A represent data dependencies among the nodes. The operands are conveyed from one node to another in data packets called tokens via the arcs. 15

16 Dataflow Graph a b (a+b) - (a*b) + * - 16

17 1 ready to fire 2 4 ready to fire + * - Fall

18 ready to fire + * ready to fire - 18

19 * ready to fire - 19

20 4 + *

21 b a 2 c * * 2 2 * neg - sqrt / /

22 Dataflow Computation Data are stored in the instructions i.e., no shared memory. Data are passed among instructions as tokens. An instruction independent of other instructions can begin its execution as soon as it is ready to be fired e.g., firing rules for static and dynamic environments. 22

23 An Example (b) (c) α + ( ) 1 γ /1 β - ( ) ( ) γ /2 γ * ( ) ( ) δ /1 a a = (b+1) * (b+c) 23