This application is related to co-pending patent applications titled “INTERCONNECTION DEVICE WITH INTEGRATED STORAGE” and identified by Ser. No. 10/184,609, “MEMORY INTERFACE WITH FRACTIONAL ADDRESSING” and identified by Ser. No. 10/184,582, “SCHEDULER FOR STREAMING VECTOR PROCESSOR” and identified by Ser. No. 10/184,772, “METHOD OF PROGRAMMING LINEAR GRAPHS FOR STREAMING VECTOR COMPUTATION” and identified by Ser. No. 10/184,743, which are filed on even day herewith and are hereby incorporated herein by reference.
This invention relates generally to the field of computer processors. More particularly, this invention relates to a re-configurable, streaming vector processor.
Many new applications being planned for mobile devices (multimedia, graphics, image compression/decompression, etc.) involve a high percentage of streaming vector computations. The computation rate of these applications often exceeds that which the best general purpose CPU's can deliver. Therefore, it is desirable to find a means to improve the performance of the computation engine present in such devices to meet the computational requirements of these new applications.
Simultaneously, the nature of these new applications is that the standards and the best algorithms for complying with the standards are constantly changing, requiring a solution that is programmable and easy to program. Moreover, time to market pressures are increasing. One method for addressing this issue is to increase the reuse of previous investments in software and hardware. Reuse of hardware across multiple products is best promoted through programmability. Reuse of software is promoted through the use of a consistent programming model across multiple implementations of a device so that binary compatibility is maintained.
One attempt to satisfy this need is the use of hardware accelerators. These fall short of solving the problem because they have limited reprogramming capability. Those hardware accelerators that are not fixed in function allow only for changes in the parameters of the functions they execute rather than a change in the type or ordering of functions.
Programmable solutions exist in the form of vector processors, digital signal processors, SIMD processors and VLIW processors. These solutions fall short due to limitations in their programming models which cause them to be difficult to program and make it difficult to maintain a consistent programming model across all generations of hardware. Limitations in their programming models include: programmer visibility of the data-path pipeline, memory width and latency, data alignment in memory, and explicit resource dependencies.
The novel features believed characteristic of the invention are set forth in the appended claims. The invention itself, however, as well as the preferred mode of use, and further objects and advantages thereof, will best be understood by reference to the following detailed description of an illustrative embodiment when read in conjunction with the accompanying drawing(s), wherein:
While this invention is susceptible of embodiment in many different forms, there is shown in the drawings and will herein be described in detail one or more specific embodiments, with the understanding that the present disclosure is to be considered as exemplary of the principles of the invention and not intended to limit the invention to the specific embodiments shown and described. In the description below, like reference numerals are used to describe the same, similar or corresponding parts in the several Views of the drawings.
The Re-configurable Streaming Vector Processor (RSVP) of the present invention is a coprocessor that performs vector operations—i.e. a set of identical operations on a sequence of data elements. It is designed to enhance the performance of an embedded general-purpose processor (the host processor) by performing high speed vector operations. In the RSVP programming model, the specification of the vector operation is split into two components: access and computation.
In one embodiment of the invention, a re-configurable, streaming vector processor is provided which includes a number of function units, each having one or more inputs for receiving data values and an output for providing a data value, a re-configurable interconnection-switch and a micro-sequencer. The re-configurable interconnection-switch includes one or more links, each link operable to couple an output of a function unit to an input of a function unit as directed by the micro-sequencer. The vector processor also includes one or more input-stream units for retrieving data from memory. The input-stream units are directed by a host processor and have a defined interface to the host processor. The vector processor also includes one or more output-stream units for writing data to memory, also with a defined interface to the host processor.
In a further embodiment, the re-configurable interconnection-switch includes a memory for storing intermediate data values.
In the preferred embodiment, the defined interface of the input-stream unit forms a first part of the programming model. The instructions, which are stored in a memory in the sequence that directs the re-configurable interconnection-switch, form a second part of the programming model.
An exemplary embodiment of RVSP hardware 100 is shown in
The architecture of the exemplary RSVP described above facilitates a separation of the operations of vector access and vector computation.
Vector access, performed by an input or output stream unit, consists of describing the location, shape, and type of each input and output vector that is part of the vector operation. In the preferred embodiment, these properties are described through two or more of the parameters:
In addition to the input and output vectors, the vector processor may include a number of scalar and accumulator registers whose initial values may be specified by the programmer. These registers are used within the vector computation. In the case of the accumulators, the values of the registers are allowed to change during the computation and may be accessed for later use. The vector access portion of the programming model is described in the programming language used for the host processor and is executed on the host.
Vector computation consists of the partially ordered set of operators to be applied to the elements of the input vectors, scalar registers, and accumulators to derive each output vector element. In the programming model of the present invention, this is done via a linearized representation of a data-flow graph of the computation. In a data-flow graph, each node in the graph is denoted using a node descriptor that specifies the operation to be performed by the node and the nodes from which its input data are obtained. There is no explicit naming of registers to pass data between operators as in other CPU's. An example computation has the C language description:
void quant (short *out, short *in, int n, short qp)
A corresponding data-flow graph is shown in
A linearized form of the data flow graph is given by:
This exemplary linearized flow form uses the functional operations:
The function unit preferably performs a variety of other functional operations including vector element addition (vadd) and accumulation (vadda). Prior to execution, the linearized graph is scheduled onto the RSVP data path. The data path is re-configurable in each clock cycle. The function units may be aggregated, that is subsets of them can be combined to form larger function units. The function unit interconnection allows for arbitrary pipelining of the function units.
The RSVP promotes the goals of high performance and quick time to market through its programming model. Since it is a coprocessor, the RSVP preferably uses a single-core programming model. Dual-core solutions, such as that used in general purpose CPU/DSP combinations, tend to be much more difficult to program. This is because with these types of solutions, the programmer must employ two different sets of programming tools and must explicitly deal with the synchronization between the CPU and DSP.
Within the programming model of the present invention, the vector access description is separate from the vector computation description. Thus, the programmer does not have to deal with intermingling of the two concerns. Because the vector access is described only in terms of five parameters, the programmer may avoid dealing with issues of data alignment and padding, memory bus width or memory latency. The underlying vector access hardware handles these issues. In this way, the vector access description remains constant, no matter the implementation of the memory subsystem or vector access hardware. Not only does this simplify the programmer's task, but it also promotes binary code compatibility in that the RSVP binary code does not have to be altered to reflect changes in those implementations.
The vector computation description, being in the form of a data-flow graph, contains no information specific to the implementation of the RSVP data path. Excepting use of accumulators and vector stream units (VSUs), the RSVP is free of any resource dependencies. In particular, it lacks the explicit naming of registers to pass data between operators. This removes the burden from the scheduler, making it easier for the scheduler to achieve an optimum schedule. As a result, the data path can change from a scalar data path, to one that is super-scalar, VLIW or SIMD-like, transparent to the programmer and without a change in the RSVP binary code.
The separation of the vector access description and the vector computation description in the programming model is illustrated in
The RSVP hardware takes advantage of several aspects of the programming model in order to improve performance. Due to the separation of vector access and computation, the hardware for each operates asynchronously with respect to the other. As a result, the vector access hardware can proceed ahead of the computation, fetching data before it is needed and thus hiding at least a portion of the memory latency.
The vector access description is succinct enough that all information is held in a small number of registers in the access hardware. These registers are accessible to the host processor. Likewise, RSVP data flow graphs are architecturally limited to a fixed number of nodes (256, for example), such that the RSVP micro-sequencer memory is large enough to hold the entire linearized form of the data flow graph. The advantage of this approach is that the hardware never needs to fetch instructions to determine how to perform the address calculations or the vector computation. This eliminates instruction fetch from the memory bandwidth required to service the RSVP computation.
Since the vector computation is specified as a data flow graph, containing few resource dependencies, the RSVP data path is unlike the data path of other CPUs. Most DSP, SIMD, VLIW and vector processor devices are unable to connect the function units of their data path in an arbitrary order. None have function units that may be aggregated.
The composition of a link of an exemplary interconnection switch is shown in
In a further embodiment, the storage access switch 504 and the output selection switch 506 are combined into a single switch.
The output data token may be selected to be the data token received at the selected link input port. Preferably, the link storage register 518 allows random access, with each register having a connection 512 to the interconnection switch. In this case the output data token may be the data token that was pushed into the storage registers a specified number of pushes previously. The delay portion of the control signal 508 is used to control the storage access switch 504. If the delay is zero, input data token is coupled through the storage access switch 504 to the output selection switch 506. Otherwise, the appropriate data token from the link storage registers is coupled through the storage access switch 504 to the output selection switch 506. The outputs are coupled to all of the interconnection switch outputs or to a subset of the interconnection switch outputs.
If one link is coupled only to a subset of the device inputs, one or more other links are provided that are coupled to the remainder of the device inputs. The control signal 508 also includes a destination address that controls the output selection switch 506 to select a link output port. In this manner, any input to the link can be routed to any link output. Also, any input can be “pushed” into the link memory (store operation). The route and push can occur simultaneously. Alternatively, the fabric link can be used to “get” a stored value and route it to any of the link outputs. The mechanism for getting a value is to specify the number of stores in the past the value was pushed. This completes the Push/Get(n) storage model. In this implementation, a ‘get’ operation and a ‘route’ operation may not be performed simultaneously. In further, the operations may be performed simultaneously.
The possible actions that can take place in the link are:
The combination of unnamed storage and communication-link based storage is advantageous because its architecture parallels that of the data-flow graph, simplifying the programming, compiling and scheduling models. Further, in the preferred embodiment, the number of links is less than the sum of the number of inputs and the number of outputs. Thereby reducing the amount of hardware required.
Each link may be coupled to all of the inputs or to a subset of the inputs to the communication fabric. Similarly, each link may be coupled to all of the outputs of the interconnection switch or to a subset of the outputs. Optionally, each output may be coupled to latch to facilitate storage of the output data tokens prior to use by attached computational units.
In one embodiment, the control signal comprises a source address, a delay and a destination address. TABLE 1 describes the actions taken by the link in response to some example control signals.
When used in conjunction with a number of computational units, such as adders, multipliers, shifters, logic unit etc., the interconnection switch provides a re-configurable data-path that facilitates the implementation of computations described by data-flow graphs.
Those of ordinary skill in the art will recognize that the present invention has been described in terms of exemplary embodiments based upon the use of a particular architecture. However, the invention should not be so limited, since the present invention could be implemented using equivalent architectures. It will be further understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention.
While the invention has been described in conjunction with specific embodiments, it is evident that many alternatives, modifications, permutations and variations will become apparent to those of ordinary skill in the art in light of the foregoing description. Accordingly, the present invention is intended to embrace all such alternatives, modifications and variations as fall within the scope of the appended claims.
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