# 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)

> 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