JIT help

Note

this is from pypy --jit help

Advanced JIT options

<pypy> --jit [options] where options is a comma-separated list of OPTION=VALUE:

decay=N

amount to regularly decay counters by (0=none, 1000=max) (default 40). This value is used to reduce the JIT counters every 32 minor collections, according to the formula val *= 1.0 - (decay / 1000). This avoids JIT compilation of rare paths even on long-running programs.

disable_unrolling=N

after how many operations we should not unroll (default 200)

enable_opts=N

INTERNAL USE ONLY (MAY NOT WORK OR LEAD TO CRASHES): optimizations to enable, or all = intbounds:rewrite:virtualize:string:pure:earlyforce:heap:unroll (default all)

function_threshold=N

number of times a function must run for it to become traced from start (default 1619)

inlining=N

inline python functions or not (1/0) (default 1)

loop_longevity=N

a parameter controlling how long loops will be kept before being freed, an estimate (default 1000)

max_retrace_guards=N

number of extra guards a retrace can cause (default 15)

max_unroll_loops=N

number of extra unrollings a loop can cause (default 0)

max_unroll_recursion=N

how many levels deep to unroll a recursive function (default 7)

retrace_limit=N

how many times we can try retracing before giving up (default 0)

threshold=N

number of times a loop has to run for it to become hot (default 1039)

trace_eagerness=N

number of times a guard has to fail before we start compiling a bridge (default 200)

trace_limit=N

number of recorded operations before we abort tracing with ABORT_TOO_LONG (default 6000)

vec=N

turn on the vectorization optimization (vecopt). Supports x86 (SSE 4.1), powerpc (SVX), s390x SIMD (default 0)

vec_all=N

try to vectorize trace loops that occur outside of the numpypy library (default 0)

vec_cost=N

threshold for which traces to bail. Unpacking increases the counter, vector operation decrease the cost (default 0)

off

turn off the JIT

help

print this page

The pypyjit module can be used to control the JIT from inside pypy