1. Lecture 3: Evolution of the Uniprocessor
SIMD
VLIW
DAE
HPS
Data Flow

6. The HPS Paradigm Incorporated the following:
Aggressive branch prediction
Speculative execution
Wide issue
Out-of-order execution
In-order retirement
First published in Micro-18 (1985)
Patt, Hwu, Shebanow: Introduction to HPS
Patt, Melvin, Hwu, Shebanow: Critical issues

11. The final flexibility: Data Flow

15. Characteristics of Data Flow
Data Driven execution of inst-level Graphical code
Nodes are operators
Arcs are I/O
Only REAL dependencies constrain processing
Anti-dependencies don’t (write-after-read)
Output dependencies don’t (write-after-write)
NO sequential I-stream (No program counter)
Operations execute ASYNCHRONOUSLY
Instructions do not reference memory
(at least memory as we understand it)
Execution is triggered by presence of data

16. Why Data Flow? Why NOT Data Flow? Irregular Parallelism
Only real dependencies constrain
Anti-dependencies don’t
Sequential I-stream doesn’t (No Program Counter)
Asynchronous (NOT in the sense of un-clocked)
Why NOT Data Flow?
In one word: too much architectural state

17. Specific Problems with Data Flow
Code bloat (everything is explicit)
Code debug (asynchronous, non-deterministic flow)
Interrupt handling (providing a consistent state)
Machine diagnosis (trouble-shooting design errors)
Recursion
Large data structures
Node table overflow (cost of CAM is high)
Performance caveats
Array copy operations
Long latencies
Network (bypass paths) congestion