Plan : staticdeps: enrich
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@ -115,22 +115,36 @@ On SKX,
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#### With valgrind
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* Write a tool, valgrind-depsim, to instrument a binary to extract its
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dependencies at runtime
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* Can extract memory, register and temp-based dependencies
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* Here, only the memory dependencies are relevant -- disable the other deps.
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* Instrument binary:
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* for each write, add `write_addr -> writer_pc` to a hashmap
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* for each read, fetch `writer_pc` from hashmap
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* if found, add a dependency `reader_pc -> writer_pc`
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* use the process' memory map to translate PC to addresses inside ELF files
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* At the end, write deps file:
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* `#occur, src_elf_pc, src_elf_path, dst_elf_pc, dst_elf_path`
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* Run for each binary in genbenchs
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* Takes about 1h on 30 parallel cores on Pinocchio; heavy memory usage
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Then, compare with staticdeps: `eval/vg_depsim.py` script.
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* For each binary in genbenchs,
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* use genbench's bb split/occurrences to retrieve basic blocks
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* for each BB with more than 10% of max BB hits,
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* predict deps with staticdeps
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* check which dependencies are found/missed from the instrumented ones
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* limitation: will only find deps from/to the same BB! Dependencies leaving
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a BB are discarded.
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* cache the result: fast, but we're dealing with 3500 files.
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* translate staticdeps' periodic deps to PC deps, discard the `iter`
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parameter
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* for each dependency from the depsim results that occurs inside this BB,
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* check if found or missed, append to a list
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* score: `|found| / (|found| + |missed|)`. Discards occurrences.
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* limitation: will only find deps from/to the same BB! Dependencies leaving
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a BB are discarded.
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* Result: about 38% of deps found.
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* Result: about 38% of deps found; 44% if weighting by occurrences
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* Cause: kernels executed in loops.
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* No dependency in the kernel
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@ -146,10 +160,41 @@ On SKX,
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* Fix: introduce dependency lifetime
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* timestamp = instructions executed (VG instrumentation, added up at the
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end of each BB)
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* lifetime fixed to 1024 instructions
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* lifetime fixed to 1024 instructions, order of magnitude of a ROB
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* dependencies are discarded if written to more than a lifetime ago
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* Result: about (?? TODO) of deps found
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* Result: about 58% of deps found; same if weighing.
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* If lifetime lowered to 512, about 56% of deps found, or 63% if weighing.
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* Results are quite similar, lowering the lifetime further makes no
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particular sense.
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Raw results:
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```
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In [123]: res_success(res_life512)
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Out[123]: 0.5640902544407105
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In [124]: res_success(res_life1024)
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Out[124]: 0.5761437608875034
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In [125]: res_success(res_nolife)
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Out[125]: 0.38143868803578085
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In [126]: res_success_weight(res_life512)
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Out[126]: 0.6347271857382266
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In [127]: res_success_weight(res_life1024)
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Out[127]: 0.5817404277466787
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In [128]: res_success_weight(res_nolife)
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Out[128]: 0.4397921976192802
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```
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* The results are reasonable, but not all the deps are caught
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* As argued above, will never see aliasing; important in plenty of cases.
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* eg. if the compiler allocates `%rcx = A[i]` and `%rdx = A[i+2]` for some
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reason, dependencies will be missed.
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* As argued in previous chapter, a complete dependencies analysis would require
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a broader range: take the full scope into account
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#### With Gus
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@ -167,3 +212,9 @@ TODO ?
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* results
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* Run CesASMe on the no-memdeps suite with uiCA and uiCA+staticdeps
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* results
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* Although not all dependencies are detected [paragraph above], the "important"
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ones seem to be detected: this is the most critical property for throughput
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analysis
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* but might not be true for other applications that require dependencies
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detection
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