Talk:Distributed Shared Memory

Here is the page where we will be discussing the DSM readings.

IVY

Anil: What were the key characteristics of IVY? What exactly did Kai Li build?

Alireza : IVY was a software based DSM system that's been developed to allow users share their local memories in a distributed manner. IVY was designed to be used in loosely coupled environments. It had five main modules including memory allocation, process management, initialization, remote operation and memory mapping. The main advantage of IVY was gaining performance in parallel applications comparing.

Alireza :(Question) Name some of the applications that you would think benefit from using IVY environment? Distributed Database system is the one that is mentioned in the dissertation. Thinks of something different.

Azalia:(Answer) Some of the current sample applications can be (CRM) Customer Relationship Management or (ERP) Enterprise Resource Planning applications that serve multiple users across an organization.Another example, imagine a billing system that has to calculate the telephone bills of thousands of customers can benefit from this environment by calculating the bill of multiple customers at the same time on different machines distributed across the network. Even though, each customer bill calculation can be done separately, using a shared memory space for reading input values like cost per minute, or cost per text message can be very useful. In addition, since each customer bill is a separate object the write operation is done in different pages of the shared memory and even using multiple writer algorithm, in this case, does not introduce any concurrency issue.

Current DSM systems?

Anil: What is a current production system that uses distributed shared memory? What about the underlying problem makes DSM a good technological fit?

Azalia:(Answer) What is a current production system that uses distributed shared memory? Any application with complex independent steps that can be parallelized would be suitable for DSM environment. Some of the current sample applications can be (CRM) Customer Relationship Management or (ERP) Enterprise Resource Planning applications that serve multiple users across an organization. What about the underlying problem makes DSM a good technological fit? Apart from DSM there are alternative methods for using in distributed environment (e.g. RPC and message passing), they have some inadequacies that DSM has been introduced to address them. For instance, message passing and RPC, have difficulties in sending complex data structures and pointers over the network due to different memory address spaces. The distributed shared memory can be a solution of this problem since all the processors share the same memory address space. In addition, if we consider current RPC technologies like Web Services, we'll realize that for each task we have to pack and send a lot of XML data around. With DSM we can share a memory space and prevent overloading network by sending XML messages.

Colin:(Answer) Any systems with a great deal of variability in load on its processors could benefit from DSM. This is because the unified address space makes process migration, and thus load balancing, simpler. (Question) How much more efficient is the movement of data across the networks on a system that implements DSM? Does it not send a comparable amount of data on a page fault as message passing or RPC would to invoke a remote call?

Difference between DSM and NUMA?

Anil What are the differences between DSM and NUMA? Under what circumstances are each appropriate?

Alireza: NUMA follows SMP paradigm where there is common memory bus for accessing shared memories. In addition, one of the most important aspects of the NUMA is that it provides different access time for the processers based on their locations. For instance local processors can have faster access to local memories. In addition, NUMA access to memory is hardware based.

Joshua Tessier: Correct me if I'm wrong but NUMA is basically a type of DSM. In a NUMA system, each processor has access to a common memory, however this common memory is distributed across each of the processors. For example, if there are 8 processors, the total memory is divided into 8 sections. As stated above, the processors have different access times to memory stores. Meanwhile, DSM is just dynamic shared memory; not a specific type like NUMA.

DSM Implementations?

Azalia:(Question) What are the different types of DSM Implementations?

Yohan:(Answer) There are 3 different types of DSM implementation. The first one is Software-level implementation which can be achieved in user-level, run-time library routine, the OS, or the programming language, for example IVY, Mermaid, Munin, etc. The second one is Hardware-level implementation which ensures that automatic replication of shared data in local memories and processors caches, transparently for software-layer, for example Memnet, Dash, SCI KSR1, etc. Since software is used in hardware support to optimize memory reference, and hardware is used in software solution such as virtual memory management, then the third one is Hybrid Level Implementation which is a combination of both implementation. Several examples of such implementation are Plus, Galactica Net, Alewife, etc.

Joshua Tessier:(Question) Does the hybrid solution hold much relevance today? From what I got in the paper, it came to light due to some limitations of the hardware/OS layers at the time. Today, we have a ton of different tools at our disposal and these limitations are no longer present. How would such a solution be divided today?

William:(Answer) While the general need for DSM systems may be reducing, when they are desired, the hybrid solution does hold some weight today. It is of course a balance of scalability vs. performance, I don't think there will ever be a day when software performance will ever exceed hardware. In order to reduce latencies a hybrid approach would be the most beneficial, but only in the correct circumstances. Software implementations make it much easier to integrate (especially those which do not modify OS functionality), while pure hardware, although costs have come down, would not be all that economical as the system would involve a lot of custom hardware and thus custom software to get the proper benefit from it. This would allow the hardware to perform certain processes, in parallel with the software, much like the internal workings of a single computer. The unfortunate downside would be for programmers, updating hardware and software simultaneously and efficiently is much more difficult than updating software alone and of course the money involved to develop such a system.