nx_paradigm_neuromorphic_gate.nx
buildroot/runtime/nx_paradigm_neuromorphic_gate.nx
about
nx_paradigm_neuromorphic_gate.nx -- honest cycle on the NEUROMORPHIC/spiking paradigm (next surfaced target).
Hypothesis (testable): event-driven SPIKING computation does FEWER ops than DENSE clock-driven, via sparsity.
Independent reference: a real op-count from a deterministic integrate-and-fire simulation -- dense polls
every neuron every timestep (M*T ops); spiking only processes actual spike events (spikes * fan-out).
Discipline (find where it LOSES too): spiking wins ONLY below the crossover firing-rate ~1/fanout; above it,
per-spike overhead beats dense. Record the REGIME where the paradigm pays, honestly -- not "spiking is
better". No hw writes (Rule 26). expect_exit: 0 license_tier: ORIGINAL
dependencies 2 imports · 0 importers
imports: nx_syscalls.nxnx_gate_verdict.nx
imported by: nobody (leaf or entry point)
call flow from main pre-order; caps 40 nodes / depth 6 declared; ↻ = already shown
structs
| none |
consts
| none |
functions
| 11 | func nm_puts(s: *u8) -> i64 { var n: i64=0; while s[n]!=(0 as u8){n=n+1} sys_write(1,s,n); return 0 } |
| 12 | func nm_num(v: i64) -> i64 { let b: *u8=sys_mmap(28); var m: i64=v; if m<0{m=0-m;sys_write(1,"-" as *u8,1)} let t: *u8=sys_mmap(28); var k: i64=0; if m==0{t[0]=48 as u8;k=1} while m>0{t[k]=(48+(m%10)) as u8;m=m/10;k=k+1} var i: i64=0; while i<k{b[i]=t[k-1-i];i=i+1} sys_write(1,b,k); return 0 } |
| 14 | func main() -> i64 |