2.6 KiB
Synopsis
A sprite compiler that targets 16-bit 65816 assembly code on the Apple IIgs computer. The sprite compiler uses informed search techniques to generate optimal code for whole-sprite rendering.
Example
The compiler takes a simple masked, sparse byte sequence which are represented by (data, mask, offset) tuples. During the search, it tracks the state of the 65816 CPU registers in order to find an optimal sequence of operations to generated the sprite data. The space of possible actions are defined by the subclasses of the CodeSequence class.
Currently, the compiler can only handle short, unmasked sequences, but it does correctly find optimal code sequences. Here is a sample of the code that the compiler generates
Data = $11
TCS ; 2 cycles
SEP #$10 ; 3 cycles
LDA #$11 ; 2 cycles
STA 00,s ; 4 cycles
REP #$10 ; 3 cycles
; Total Cost = 14 cycles
Data = $11 $22
TCS ; 2 cycles
LDA #$2211 ; 3 cycles
STA 00,s ; 5 cycles
; Total Cost = 10 cycles
Data = $11 $22 $22
TCS ; 2 cycles
LDA #$2222 ; 3 cycles
STA 02,s ; 5 cycles
LDA #$2211 ; 3 cycles
STA 01,s ; 5 cycles
; Total Cost = 18 cycles
Data = $11 $22 $11 $22
TCS ; 2 cycles
LDA #$2211 ; 3 cycles
STA 00,s ; 5 cycles
STA 02,s ; 5 cycles
; Total Cost = 15 cycles
Data = $11 $22 $33 $44 $55 $66
ADC #5 ; 3 cycles
TCS ; 2 cycles
PEA $6655 ; 5 cycles
PEA $4433 ; 5 cycles
PEA $2211 ; 5 cycles
; Total Cost = 20 cycles
Data = $11 $22 $11 $22 $11 $22 $11 $22
ADC #7 ; 3 cycles
TCS ; 2 cycles
LDA #$2211 ; 3 cycles
PHA ; 4 cycles
PHA ; 4 cycles
PHA ; 4 cycles
PHA ; 4 cycles
; Total Cost = 24 cycles
Data = ($11, 0), ($11, 160), ($11, 320)
A simple sprite three lines tall.
TCS ; 2 cycles
SEP #$10 ; 3 cycles
LDA #$11 ; 2 cycles
PHA ; 3 cycles
STA A1,s ; 4 cycles
REP #$10 ; 3 cycles
TSC ; 2 cycles
ADC #321 ; 3 cycles
TCS ; 2 cycles
SEP #$10 ; 3 cycles
LDA #$11 ; 2 cycles
PHA ; 3 cycles
REP #$10 ; 3 cycles
; Total Cost = 35 cycles
Limitations
The search is quite memory intensive and grows too fast to handle multi-line sprite data yet. Future versions will incorporate more aggressive heuristic and Iterative Deepening A-Star search to mitigate the memory usage.
License
MIT License