ASP.NET Web PDF Document Viewer/Editor Control Library

module CInterop = [<Struct; StructLayout(LayoutKind.Sequential)>] type Complex = val mutable re:double val mutable im:double new(r,i) = { re = r; im = i; } [<DllImport("CInteropDLL")>] extern Complex SumC(Complex c1, Complex c2) let c1 = CInterop.Complex(1.0, 0.0) let c2 = CInterop.Complex(0.0, 1.0) let mutable c3 = CInterop.SumC(c1, c2) printf "c3 = SumC(c1, c2) = %f + %fi\n" c3.re c3.im; The SumC prototype refers to the F# Complex value type, but since the layout in memory of the structure is the same as the corresponding C structure, the runtime passes the bits that are consistent with those expected by the C code.

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Finally, in the main() method, we initialize the number of connections to establish, create an instance of our class, and invoke the _runBenchmark() method: public static void main(String args[]) throws Exception { if( args.length == 1 ) { _numOfConnections = Integer.parseInt( args[0] ); } new CostOfConnection()._runBenchmark(); } }// end of program Results of a run on my machine for ten connections are as follows: B:\code\book\ch15>java CostOfConnection 10 Establishing 10 connection(s) and closing them On an average it took 1641 ms (number of runs = 130.) As you can see, it took almost 164 milliseconds (approximately 1/6 of a second) to establish and close a connection. Closing a connection usually takes a negligible amount of time, so the entire time of 164 milliseconds can be approximately attributed to the act of establishing a connection. This can be very costly if you consider the case of thousands of users performing many small requests, with each request resulting in the creation and destruction of a connection. Also, since establishing a connection involves forking a process on UNIX and creating a new thread on Windows, it can quickly exhaust system resources. For example, on my PC, I could not establish more than 132 simultaneous connections at a time. The next section shows how the technique of connection pooling addresses this problem.

A critical aspect in dealing with PInvoke is to ensure that values are marshalled correctly between managed and native code, and vice versa. The memory layout of a structure does not depend on the order of the fields only. Compilers often introduce padding to align fields to memory addresses so that access to fields requires fewer memory operations since CPUs load data into registers with the same strategy. Padding may speed up access to the data structure, though it introduces inefficiencies in memory usage since there may be gaps in the structures leading to allocated but unused memory. Consider, for instance, the following C structure: struct Foo { int i; char c; short s; }; Depending on compiler decision, it may occupy from 8 up to 12 bytes on a 32-bit architecture. The most compact version of the structure uses the first four bytes for i, a single byte for c, and two more bytes for s. If the compiler aligns fields to addresses that are multiples of four, then the integer i occupies the first slot, four more bytes are allocated for c (though only one is used), and the same happens for s. Padding is a common practice in C programs, and since it may affect performance and memory usage, compilers provide directives to instruct the compiler about padding. It is possible to have data structures with different padding strategies running within the same program. The first step to be faced when using PInvoke to access native code is to find the definition of data structures, including information about padding. Then it is possible to annotate F# structures to have the same layout as the native ones, and the CLR can automate the marshalling of data. It is important to note that it is

The author of this chapter originally discovered the capturing of the rendered output stream capability Tip