GridRPC


GridRPC is Remote Procedure Call over a grid. This paradigm has been proposed by the GridRPC working group of the Open Grid Forum, and an API has been defined in order for clients to access remote servers as simply as a function call. It is used among numerous Grid middleware for its simplicity of implementation, and has been standardized by the OGF in 2007.
For interoperability reasons between the different existing middleware, the API has been followed by a document describing good use and behavior of the different GridRPC API implementations. Works have then been conducted on the GridRPC Data Management, which has been standardized in 2011.

Scope

The scope of this standard is to offer recommendations for the implementation of middleware. It deals with the following topics:
Among existing middleware and application programming approaches, one simple, powerful, and
flexible approach consists in using servers available in different administrative domains through the classical
client-server or Remote Procedure Call paradigm. Network Enabled Servers implement this model,
which is also called GridRPC. Clients submit computation requests to a resource broker whose goal is to find a
server available on the Grid. Scheduling is frequently applied to balance the work among the servers and a list of
available servers is sent back to the client; the client is then able to send the data and the request to one of the
suggested servers to solve its problem. Thanks to the growth of network bandwidth and the reduction of network latency,
small computation requests can now be sent to servers available on the Grid. To make effective use of today's scalable
resource platforms, it is important to ensure scalability in the middleware layers as well. This service-oriented
approach is not new.
Several research projects have targeted this paradigm in the past. The main middleware implementing the API are DIET, NetSolve/GridSolve, Ninf, but some other environments use it like the SAGA interface from the OGF, and without the standardized API calls, like OmmiRPC, XtremWeb. The RPC model over the internet has
also been used for several applications. Transparently through the Internet, large optimization problems can be solved
using different approaches by simply filling a web page for remote image processing computations, the use of mathematical libraries or studies on heuristics and resolution methods for sparse linear algebra like GridTLSE. This approach of providing computation services through the Internet is also highly close to the Service Oriented Computing
paradigm, and is the core of the Cloud computing.

Standardization and GridRPC API presentation

One simple, yet effective, mean to execute jobs on a computing grid is
to use a GridRPC middleware, which relies on the GridRPC
paradigm. For each request, the GridRPC middleware manages the management of the
submission, of the input and output data, of the execution of the job
on the remote resource, etc. To make available a service, a programmer
must implement two codes: a client, where data are defined and which
is run by the user when requesting the service, and a server, which
contains the implementation of the service which is executed on the
remote resource.
One step to ease the development of such codes conducted to define a
GridRPC API, which has been proposed as a draft in November 2002 and which is an Open Grid Forum standard since
September 2007. Thus a GridRPC source code which does not involve specific middleware data can be compiled and
executed with any GridRPC compliant middleware.
Due to the difference in the choice of implementation of the GridRPC
API, a document describing the interoperability between GridRPC
middleware has also been written. Its main
goals are to describe the difference in behaviour of the GridRPC
middleware and to propose a common test that all GridRPC middleware
must pass.
Discussions have then been undertaken on the data management within
GridRPC middleware. A draft of an API has been proposed during the
OGF'21 in October 2007. The motivation for this document is to provide
explicit functions to manipulate the data exchange between a
GridRPC platform and a client since the size of the data used in
grid applications may be large and useless data transfers must be
avoided; data are not always stored on the client side but may be
made available either on a storage resource or within the GridRPC
platform. Hence, a side effect is that a fully GridRPC-compliant code can be written and compiled with any GridRPC middleware implementing the GridRPC Data Management API.

GridRPC Paradigm

The GridRPC model is pictured in the following figure. Here is how communications are handled: servers register their services to a registry; when a client needs the execution of a service, it contacts the registry and the registry returns a handle to the client; then the client uses the handle to invoke the service on the server and eventually receives back the results.

GridRPC API

Mechanisms involved in the API must provide means to make synchronous
and/or asynchronous calls to a service. If the latter, clients must
also be able to wait in a blocking or non-blocking manner after the
completion of a given service. This naturally involves some data
structures and conducts to a rigorous definition of the functions of
the API.
GridRPC Data Types
Three main data types are needed to implement the API: grpc_function_handle_t is the type of variables representing a
remote function bound to a given server. Once allocated by the client,
such a variable can be used to launch the service as many times as
desired. It is explicitly invalidated by the user when not needed
anymore; grpc_session_t is the type of variables used to
identify a specific non-blocking GridRPC call. Such a variable is
mandatory to obtain information on the status of a job, in order for a
client to wait after, cancel or know the error status of a call;
grpc_error_t groups all kind of errors and returns status
codes involved in the GridRPC API.
GridRPC Functions
grpc_initialize and grpc_finalize functions are
similar to the MPI initialize and finalize calls. It is mandatory that
any GridRPC call is performed in between these two calls. They read
configuration files, make the GridRPC environment ready and finish it.
In order to initialize and destruct a function handle, grpc_function_handle_init and grpc_function_handle_destruct functions have to be
called. Because a function handle can be dynamically associated to a
server, because of resource discovery mechanisms for example, a call
to grpc_function_handle_default let to postpone the server
selection until the actual call is made on the handle.
grpc_get_handle let the client retrieve the function handle
corresponding to a session ID that has
been previously performed.
Depending on the type of the call, blocking or non-blocking, the
client can use the grpc_call and grpc_call_async
function. If the latter, the client possesses after the call a session
ID which can be used to respectively probe or wait for completion,
cancel the call and check the error status of a non-blocking call.
After issuing a unique or numerous non-blocking calls, a client can
use: grpc_probe to know if the execution of the service has
completed; grpc_probe_or to know if one of the previous
non-blocking calls has completed; grpc_cancel to cancel a
call; grpc_wait to block until the completion of the
requested service; grpc_wait_and to block until all services
corresponding to session IDs used as parameters are finished; grpc_wait_or to block until any of the service corresponding to
session IDs used as parameters has finished; grpc_wait_all to
block until all non-blocking calls have completed; and grpc_wait_any to wait until any previously issued non-blocking
request has completed.

GridRPC Compliant Code

Talk about the lib against which a code must compile and give a basic example

GridRPC documents