HPJava stands for ?high performance java?. Java already provides parallelism through threads. But that model of parallelism can only be easily exploited on shared memory computers. HPJava is targetted at distributed memory parallel computers (most likely, networks of PCs and workstations).
??????????? ??Java is designed to meet the chalanges of application development on the context of heterogeneous, network-wide distributed environments. Paramaount amoung these chalanges is secure delivery of applications that consume the minimum of systems resources, can run on any hardware and software platform, can be extended dynamically.?
Several of these concerns are mirrored in developments in the High Prerformance Computing world over a number of years. A decade ago the focus of interest in the parallel computing community was on parallel hardware. A parallel computer was typically built from specialized processers through a proprietary high-performance communication switch. If the machine also had to be programmed in a proprietary language, that was an acceptable price for the benefits of using a supercomputer. This attitude was not sustainable as one parallel architecture gave way to another, and cost of porting software became exorbitant. For several years now, portability across platforms had been a central concern in parallel computing.
HPJava is a programming language extended from Java to support parallel programming, especially (but not exclusively) data parallel programming on message passing and distributed memory systems, from multi-processor systems to workstation clusters.
Although it has a close relationship with HPF, the design of HPJava does not inherit the HPF programming model. Instead the language introduces a high-level structured SPMD programming style--the HPspmd model. A program written in this kind of language explicitly coordinates well-defined process groups. These cooperate in a loosely synchronous manner, sharing logical threads of control. As in a conventional distributed-memory SPMD program, only a process owning a data item such as an array element is allowed to access the item directly. The language provides special constructs that allow programmers to meet this constraint conveniently.
Besides the normal variables of the sequential base language, the language model introduces classes of global variables that are stored collectively across process groups. Primarily, these are distributed arrays. They provide a global name space in the form of globally subscripted arrays, with assorted distribution patterns. This helps to relieve programmers of error-prone activities such as the local-to-global, global-to-local subscript translations which occur in data parallel applications.
In addition to special data types the language provides special constructs to facilitate both data parallel and task parallel programming. Through these constructs, different processors can either work simultaneously on globally addressed data, or independently execute complex procedures on locally held data. The conversion between these phases is seamless.
??????????? In the traditional SPMD mold, the language itself does not provide implicit data movement semantics. This greatly simplifies the task of the compiler, and should encourage programmers to use algorithms that exploit locality. Data on remote processors is accessed exclusively through explicit library calls. In particular, the initial HPJava implementation relies on a library of collective communication routines originally developed as part of an HPF runtime library. Other distributed-array-oriented communication libraries may be bound to the language later. Due to the explicit SPMD programming model, low level MPI communication is always available as a fall-back. The language itself only provides basic concepts to organize data arrays and process groups. Different communication patterns are implemented as library functions. This allows the possibility that if a new communication pattern is needed, it is relatively easily integrated through new libraries.
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