dsPIC语言工具库：Microchip开发资源详解

dsPIC工具库

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"dsPIC语言工具库是Microchip Technology Inc.为dsPIC微控制器提供的软件开发支持，包含了丰富的库函数和工具，旨在简化基于dsPIC的嵌入式系统开发过程。这些工具库通常包括数学运算、通信协议、定时器管理、中断处理等各种功能模块，为开发者提供了高效且可靠的代码构建基础。" dsPIC语言工具库是专为Microchip的dsPIC系列数字信号控制器（Digital Signal Controller）设计的一套综合开发资源，它涵盖了编程语言（如C和汇编）、编译器、调试器以及一系列预编译的库函数。这些库函数通常经过优化，能够充分利用dsPIC的硬件特性，比如高速计算能力、浮点运算单元和并行处理结构。该工具库中的核心组成部分可能包括以下几点： 1. **编译器**：如MPLAB XC编译器，用于将高级语言代码转换为可执行的机器代码，支持C和汇编语言，通常具有优化选项以提高代码效率。 2. **链接器和 librarian**：链接器将编译后的对象文件合并成单一的可执行文件，而librarian则管理库文件，使得开发人员可以方便地导入和导出库函数。 3. **调试工具**：如MPLAB IDE和MPLAB ICD（In-Circuit Debugger），它们提供图形用户界面和硬件接口，用于在目标系统上进行代码调试。 4. **库函数**：包含基础数学运算（如三角函数、指数和对数）、I/O操作、中断服务例程、定时器管理、串行通信（如UART、SPI、I2C）等，以及特定应用领域的库（如电机控制、ADC/DAC转换、PWM生成等）。 5. **示例代码和教程**：为了帮助开发者快速上手，工具库通常会提供大量示例代码和教程，涵盖各种应用场景，帮助理解如何有效利用库函数。 6. **性能优化**：dsPIC语言工具库中的函数往往针对dsPIC架构进行了优化，以充分利用其硬件特性，例如硬件乘法器和浮点单元，从而实现更快的计算速度。 7. **版本更新和支持**：Microchip会定期更新和维护这些工具库，以修复已知问题，增加新功能，兼容新的dsPIC器件，并保持与最新技术标准的同步。在使用dsPIC语言工具库时，开发者需要注意的是，虽然库函数提供了便利，但确保应用程序符合具体规格的责任仍在于开发人员。此外，Microchip声明不承担任何关于信息准确性或使用这些信息可能导致的专利或其他知识产权侵权的责任。使用Microchip产品作为生命支持系统的关键组件需获得Microchip的书面批准，且不授予任何隐性或明示的知识产权许可。最后，Microchip的各种品牌和商标应按照其使用规则来使用，尊重知识产权。

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dsPIC

™

Language Tools Libraries

DS51456A-page 12 Advance Information  2004 Microchip Technology Inc.

2.3.7 Overflow and Saturation Handling

The DSP Library performs most computations using 9.31 saturation, but must store the

output of the function in 1.15 format. If during the course of operation the accumulator

in use saturates (goes above 0x7F FFFF FFFF or below 0x80 0000 0000), the

corresponding saturation bit (SA or SB) in the Status register will be set. This bit will

stay set until it is cleared. This allows you to inspect SA or SB after the function

executes and to determine if action should be taken to scale the input data to the

function.

Similarly, if a computation performed with the accumulator results in an overflow (the

accumulator goes above 0x00 7FFF FFFF or below 0xFF 8000 0000), the

corresponding overflow bit (OA or OB) in the Status register will be set. Unlike the SA

and SB status bits, OA and OB will not stay set until they are cleared. These bits are

updated each time an operation using accumulator is executed. If exceeding this

specified range marks an important event, you are advised to enable the Accumulator

Overflow Trap via the OVATE and OVBTE bits in the INTCON1 register. This will have

the effect of generating an Arithmetic Error Trap as soon as the Overflow condition

occurs, and you may then take the required action.

2.3.8 Integrating with Interrupts and an RTOS

The DSP Library may easily be integrated into an application which utilizes interrupts

or an RTOS, yet certain guidelines must be followed. To minimize execution time, the

DSP Library utilizes DO loops, REPEAT loops, modulo addressing and bit-reversed

addressing. Each of these components is a finite hardware resource on the dsPIC30F

DSC, and the background code must consider the use of each resource when

disrupting execution of a DSP Library function.

When integrating with the DSP Library, you must examine the Function Profile of each

function description to determine which resources are used. If a library function will be

interrupted, it is your responsibility to save and restore the contents of all registers used

by the function, including the state of the DO, REPEAT and special addressing

hardware. Naturally this also includes saving and restoring the contents of the

CORCON and Status registers.

2.3.9 Rebuilding the DSP Library

A batch file named makedsplib.bat is provided to rebuild the DSP library. The

MPLAB C30 compiler is required to rebuild the DSP library, and the batch file assumes

that the compiler is installed in the default directory, c:\pic30_tools. If your

language tools are installed in a different directory, you must modify the directories in

the batch file to match the location of your language tools.

DSP Library

 2004 Microchip Technology Inc. Advance Information DS51456A-page 13

2.4 VECTOR FUNCTIONS

This section presents the concept of a fractional vector, as considered by the DSP

Library, and describes the individual functions which perform vector operations.

2.4.1 Fractional Vector Operations

A fractional vector is a collection of numerical values, the vector elements, allocated

contiguously in memory, with the first element at the lowest memory address. One word

of memory (two bytes) is used to store the value of each element, and this quantity

must be interpreted as a fractional number represented in the 1.15 data format.

A pointer addressing the first element of the vector is used as a handle which provides

access to each of the vector values. The address of the first element is referred to as

the base address of the vector. Because each element of the vector is 16 bits, the base

address must be aligned to an even address.

The one dimensional arrangement of a vector accommodates to the memory storage

model of the device, so that the n-th element of an N-element vector can be accessed

from the vector's base address BA as:

BA + 2(n-1), for 1 ≤ n ≤ N.

The factor of 2 is used because of the byte addressing capabilities of the dsPIC30F

device.

Unary and binary fractional vector operations are implemented in this library. The

operand vector in a unary operation is called the source vector. In a binary operation

the first operand is referred to as the source one vector, and the second as the source

two vector. Each operation applies some computation to one or several elements of the

source vector(s). Some operations produce a result which is a scalar value (also to be

interpreted as a 1.15 fractional number), while other operations produce a result which

is a vector. When the result is also a vector, this is referred to as the destination vector.

Some operations resulting in a vector allow computation in place. This means the

results of the operation are placed back into the source vector (or the source one vector

for binary operations). In this case, the destination vector is said to (physically) replace

the source (one) vector. If an operation can be computed in place, it is indicated as such

in the comments provided with the function description.

For some binary operations, the two operands can be the same (physical) source

vector, which means the operation is applied to the source vector and itself. If this type

of computation is possible for a given operation, it is indicated as such in the comments

provided with the function description.

Some operations can be both self applicable and computed in place.

All the fractional vector operations in this library take as an argument the cardinality

(number of elements) of the operand vector(s). Based on the value of this argument the

following assumptions are made:

a) The sum of sizes of all the vectors involved in a particular operation falls within

the range of available data memory for the target device.

b) In the case of binary operations, the cardinalities of both operand vectors must

obey the rules of vector algebra (particularly, see remarks for the

VectorConvolve and VectorCorrelate functions).

c) The destination vector must be large enough to accept the results of an

operation.

dsPIC

™

Language Tools Libraries

DS51456A-page 14 Advance Information  2004 Microchip Technology Inc.

2.4.2 User Considerations

a) No boundary checking is performed by these functions. Out of range cardinalities

(including zero length vectors) as well as nonconforming use of source vector

sizes in binary operations may produce unexpected results.

b) The vector addition and subtraction operations could lead to saturation if the sum

of corresponding elements in the source vector(s) is greater than 1-2

-15

smaller than -1.0. Analogously, the vector dot product and power operations

could lead to saturation if the sum of products is greater than 1-2

-15

or smaller

than -1.0.

c) It is recommended that the Status register (SR) be examined after completion of

each function call. In particular, users can inspect the SA, SB and SAB flags after

the function returns to determine if saturation occurred.

d) All the functions have been designed to operate on fractional vectors allocated

in default RAM memory space (X-Data or Y-Data).

e) Operations which return a destination vector can be nested, so that for instance

if:

a = Op1 (b, c), with b = Op2 (d), and c = Op3 (e, f), then

a = Op1 (Op2 (d), Op3 (e, f))

2.4.3 Additional Remarks

The description of the functions limits its scope to what could be considered the regular

usage of these operations. However, since no boundary checking is performed during

computation of these functions, you have the freedom to interpret the operation and its

results as it fits some particular needs.

For instance, while computing the VectorMax function, the length of the source vector

could be greater than numElems. In this case, the function would be used to find the

maximum value only among the first numElems elements of the source vector.

As another example, you may be interested in replacing numElems elements of a

destination vector located between N and N+numElems-1, with numElems elements

from a source vector located between elements M and M+numElems-1. Then, the

VectorCopy function could be used as follows:

fractional* dstV[DST_ELEMS] = {...};

fractional* srcV[SRC_ELEMS] = {...};

int n = NUM_ELEMS;

int N = N_PLACE; /* NUM_ELEMS+N

≤ DST_ELEMS */

int M = M_PLACE; /* NUM_ELEMS+M

≤ SRC_ELEMS */

fractional* dstVector = dstV+N;

fractional* srcVector = srcV+M;

dstVector = VectorCopy (n, dstVector, srcVector);

Also in this context, the VectorZeroPad function can operate in place, where now

dstV = srcV, numElems is the number of elements at the beginning of source vector

to preserve, and numZeros the number of elements at the vector tail to set to zero.

Other possibilities can be exploited from the fact that no boundary checking is

performed.

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