# 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