Memory operation
I'm trying to implement a "load in array" operation, so giving an array filled with some values to the "compute" function, which reads and returns the content of array[4]. The generated code seems correct, but the returned value is not:
static void test2()
{
MIR_context_t fContext = MIR_init();
MIR_module_t fModule = MIR_new_module(fContext, "Faust");
// Create 'compute' function
MIR_type_t res_type = MIR_T_D;
MIR_item_t fCompute = MIR_new_func(fContext, "compute", 1, &res_type, 1, MIR_T_P, "real_heap");
// Get 'heap' argument
MIR_reg_t HEAP = MIR_reg(fContext, "real_heap", fCompute->u.func);
// Create a local
MIR_reg_t VAR1 = MIR_new_func_reg(fContext, fCompute->u.func, MIR_T_D, "VAR1");
// Create and set 'index'
MIR_reg_t INDEX = MIR_new_func_reg(fContext, fCompute->u.func, MIR_T_I64, "INDEX");
MIR_append_insn(fContext, fCompute,
MIR_new_insn(fContext,
MIR_MOV,
MIR_new_reg_op(fContext, INDEX),
MIR_new_int_op(fContext, 4)));
// Get the 'heap' content at 'index'
MIR_append_insn(fContext, fCompute,
MIR_new_insn(fContext, MIR_DMOV,
MIR_new_reg_op(fContext, VAR1),
MIR_new_mem_op(fContext, MIR_T_D, 0, HEAP, INDEX, 1)));
MIR_append_insn(fContext, fCompute, MIR_new_ret_insn(fContext, 1, MIR_new_reg_op(fContext, VAR1)));
// Finish function
MIR_finish_func(fContext);
// Finish module
MIR_finish_module(fContext);
MIR_load_module (fContext, fModule);
MIR_link(fContext, MIR_set_interp_interface, import_resolver);
// Dump module
MIR_output(fContext, stderr);
// Preparing test heap with some values
double heap[8];
for (int i = 0; i < 8; i++) {
heap[i] = (double)i;
printf("Heap: %f\n", heap[i]);
}
MIR_val_t val;
MIR_interp(fContext, fCompute, &val, 1, (MIR_val_t){.a = (void*)heap});
printf("Result: %f\n", val.d);
MIR_finish(fContext);
}
Faust: module
compute: func d, p:real_heap
local d:VAR1, i64:INDEX, i64:t1
# 1 arg, 3 locals
mov INDEX, 4
add t1, real_heap, INDEX
dmov VAR1, d:(t1)
ret VAR1
endfunc
endmodule
Heap: 0.000000
Heap: 1.000000
Heap: 2.000000
Heap: 3.000000
Heap: 4.000000
Heap: 5.000000
Heap: 6.000000
Heap: 7.000000
Result: 0.000000
mov INDEX, 4 add t1, real_heap, INDEX dmov VAR1, d:(t1)
When you use index it is scaled by the last operand of MIR_new_mem_op which is 1 in your test. Therefore your MIR code reads from half of the 0th heap double (not just 4th double). Instead of
MIR_new_mem_op(fContext, MIR_T_D, 0, HEAP, INDEX, 1) you should use MIR_new_mem_op(fContext, MIR_T_D, 0, HEAP, INDEX, 8)
MIR is low level language, it is easy to make a mistake. Some people generates C code and use c2mir although it slows down compilation a lot and make JIT much bigger.
Working, thanks a lot !
So I understand that I can also write some C and use c2mir to better understand what has to be generated.
So I understand that I can also write some C and use
c2mirto better understand what has to be generated.
Yes, you can. And some people do this. Such approach makes JIT bigger and slow. Generation of code through MIR API is about 10-15 times faster than through c2mir. Although c2mir is also 10-15 times faster than gcc -O2 it was never designed to be a fast compiler.
My own plans to implement JIT for Ruby is to use MIR API directly during JIT work and c2mir for translation of C code only during building Ruby (it is an existing C code implementing standard Ruby methods). During JIT work, the translated C code can be inlined with MIR code generated by MIR API to use inlining and to optimize the result inlined code.
I plan to directly use MIR API. My point what to say: I can write some simple C tests, compile them using c2mir to understand what has to be generated, then directly generate MIR.
I plan to directly use MIR API. My point what to say: I can write some simple C tests, compile them using c2mir to understand what has to be generated, then directly generate MIR.
I like your approach. I guess it can work for you. The only trouble is that MIR code generated from C might be hard to read and there are a lot of dead code (it is mostly results of assign-stmts which are never used).