Algorithm-to-hardware system and method for creating a...

Computer-aided design and analysis of circuits and semiconductor – Nanotechnology related integrated circuit design

Reexamination Certificate

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C716S030000

Reexamination Certificate

active

06785872

ABSTRACT:

FIELD OF THE INVENTION
This invention relates to creating a digital circuit. More particularly, the invention relates to converting an algorithm rendered in a programming language into an actual hardware implementation consisting of the digital circuit.
BACKGROUND OF THE INVENTION
Various persons have previously attempted to address the long-felt need for an easy approach to creating hardware designs. The prior art evidences two divergent approaches for designing actual implementations of digital hardware.
One prior art approach recognizes that the development of digital hardware would be available to a wider population if hardware designs could be rendered in a standard high-level programming language, which is more universally known, easier to use, and more frequently employed than HDLs. One such high-level programing language is ANSI C. Others, many of which have several extensions, are: APL, Ada, Algol, B, Basic, Kernighan & Ritchie C, C++, CLOS, COBOL, Clu, Common Lisp, Coral, Dylan, Eiffel, Emacs Lisp, Forth, Fortan, IDL, Icon, Java, Jovial, Lisp, LOGO, ML, Modula, Oberon, Objective C, PL/I, PL/M, Pascal, Postscript, Prolog, Python, RTL, Rexx, SETL, Simula, Sather, Scheme, Smalltalk, Standard ML, TCL, and TRAC.
Prior art attempts to base computer aided hardware design tools on high-level programing languages have generally suffered from a number of shortcomings. In order to represent an algorithm in a high-level language, the designer must typically sacrifice direct control over the circuits generated by the associated design tools. Because the high-level language has no mechanism to represent specially constructed adders, multipliers and the like, the resulting tool-generated circuit typically has poor performance relative to what a hardware designer could achieve given the same algorithm. Furthermore, the tool-generated circuits may be inefficiently large compared to a human-designer created circuit. This results from the fact that hardware generated using prior art computer aided hardware design tools is typically based on simple line-by-line, table-driven translation and lacks the global optimizations that can be perceived by the human designer. In addition, the high-level language may lack the ability to specify non-standard sized registers, bit-serial communication paths and other design constructs known to produce smaller designs. Finally, in an attempt to approach human-designer quality results, the user of the high-level language based toolset might have to resort to a much lower-level algorithm specification, thus sacrificing the clarity of representation that is a primary benefit of this prior art toolset.
The inability of the prior art to generate efficient circuits is further illustrated by the following example. In this example, an algorithm to sum ten numbers is considered. An important aspect of the numbers to be summed in this example is that they represent student exam scores and can assume values in the range of 0 to 100 inclusive. The maximum value of the exam score total, which is specified to be the sum of ten exam scores, is thus 10*100=1000. This algorithm, coded in the high-level conventional C-language, is as follows:
/* source code A */
unsigned char exam_scores[10];
unsigned short total_exam_scores( ) {
unsigned short total=0;
unsigned int i;
for (i=0;i<10;i++)
total+=exam_scores[i];
return total;
}
FIG. 7
shows a digital circuit
700
that may be generated by inputting the source code A into a prior art compiler. In this and subsequent circuit diagrams, a clocked register is denoted by a rectangular box with a double line at its input and with the &Dgr; symbol inside to denote a delay of one clock cycle. Furthermore, in circuit
700
and subsequent circuit diagrams, only the datapath logic is shown, with control logic like clocking and memory address sequencing omitted for the sake of clarity. In the source code A, an 8-bit “unsigned char” is used for the “exam_scores” variable, since “unsigned char” is the smallest data type available in C that can still hold the maximum exam score of 100. A 16-bit “unsigned short” is used for the “total” variable, since this is the smallest data type that can hold the maximum exam score total of 1000. Based on this coding, a prior art compiler would generate the circuit
700
consisting of an 8-bit wide exam score memory
710
, a 16-bit adder
720
and a 16-bit “total” register
730
. The circuit
700
, however, is far larger than optimal, because the smallest available variable sizes are larger than necessary, which results in an inefficient hardware realization.
A high-level language, i.e., PASCAL, provides the ability by way of its scalar subrange data types to specify a variable's set of assumable values, and hence its bit-width, with greater specificity than the conventional C-language. However, PASCAL has not been implemented in an algorithm-to-hardware toolset to provide optimal circuit configurations. Because of these listed shortcomings, the attempts at creating an effective tool for designing hardware using a high-level programming language have not achieved widespread use.
A second prior art approach to creating designs for digital hardware has been to create a specific hardware description language (HDL). Various commercially available HDLs have been developed, such as Verilog, VHDL, ABEL, CUPL, AHDL, MACHX, and PALASM. After a hardware design is rendered in an HDL, the HDL design is processed into a gate-level or cell-level netlist representation using one of various hardware or manufacturer-specific synthesis programs to interpret the HDL design. Then, the netlist representation is reduced to an actual hardware realization using conventional physical design tools.
HDLs and their associated computer-aided design tools have been created to be used by hardware designers and require a level of expertise in the use of the particular HDL being employed to render a hardware design. Because HDLs are difficult to learn and use, only persons who frequently design hardware typically use them. If a circuit application arises in which an HDL-representation of the algorithm is justified, the vast majority of persons must retain an expert or confront the difficult task of learning an HDL. Furthermore, these HDLs are not typically universal for the design of all target hardware technologies, since many HDLs are supported by only a single or a limited number of hardware manufacturers. Consequently, even experienced users of an HDL may not be sufficiently familiar with other HDLs to be able to render a design that can be implemented in a variety of hardware systems from a number of different hardware manufacturers.
HDLs permit a much more detailed control over the resulting hardware implementation, but often by sacrificing the clarity and supportability of the algorithm. To further illustrate this shortcoming of conventional HDLs, the previous problem of summing 10 exam scores is reconsidered. In an attempt to create a more efficient hardware realization, the algorithm specification is modified by including a language-feature present in prior art HDLs such as Verilog and VHDL, namely the ability to specify exact bit-widths of variables. Using one of a number of possible syntaxes, an integer variable whose value representation is constrained to exactly N bits is defined using the datatype “intN”. The revised algorithm for summing ten exam scores is coded in the source code B as follows:
/* source code B */
unsigned int7 exam_scores[10];
unsigned int10 total_exam_scores( ) {
unsigned int10 total=0;
unsigned int i;
for (i=0;i<10;i++)
total +=exam_scores[i];
return total;
}
The source code B uses the added bit-width language feature to specify a smaller size for the “exam_scores” and the “total” variables. In particular, a 7-bit integer type “unsigned int7” is the smallest data type available that can hold the maximum exam score of 100. Similarly, an “unsi

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