> -----Original Message----- > From: Jerin Jacob <jerinjac...@gmail.com> > Sent: Thursday, September 2, 2021 3:12 PM > To: Elena Agostini <eagost...@nvidia.com> > Cc: Wang, Haiyue <haiyue.w...@intel.com>; NBU-Contact-Thomas > Monjalon <tho...@monjalon.net>; Jerin Jacob <jer...@marvell.com>; > dpdk-dev <dev@dpdk.org>; Stephen Hemminger > <step...@networkplumber.org>; David Marchand > <david.march...@redhat.com>; Andrew Rybchenko > <andrew.rybche...@oktetlabs.ru>; Honnappa Nagarahalli > <honnappa.nagaraha...@arm.com>; Yigit, Ferruh <ferruh.yi...@intel.com>; > techbo...@dpdk.org > Subject: Re: [dpdk-dev] [RFC PATCH v2 0/7] heterogeneous computing > library > > > On Wed, Sep 1, 2021 at 9:05 PM Elena Agostini <eagost...@nvidia.com> > wrote: > > > > > > > -----Original Message----- > > > From: Wang, Haiyue <haiyue.w...@intel.com> > > > Sent: Sunday, August 29, 2021 7:33 AM > > > To: Jerin Jacob <jerinjac...@gmail.com>; NBU-Contact-Thomas > Monjalon > > > <tho...@monjalon.net> > > > Cc: Jerin Jacob <jer...@marvell.com>; dpdk-dev <dev@dpdk.org>; > > > Stephen Hemminger <step...@networkplumber.org>; David Marchand > > > <david.march...@redhat.com>; Andrew Rybchenko > > > <andrew.rybche...@oktetlabs.ru>; Honnappa Nagarahalli > > > <honnappa.nagaraha...@arm.com>; Yigit, Ferruh > > > <ferruh.yi...@intel.com>; techbo...@dpdk.org; Elena Agostini > > > <eagost...@nvidia.com> > > > Subject: RE: [dpdk-dev] [RFC PATCH v2 0/7] heterogeneous computing > > > library > > > > > > > > > > > > > -----Original Message----- > > > > From: Jerin Jacob <jerinjac...@gmail.com> > > > > Sent: Friday, August 27, 2021 20:19 > > > > To: Thomas Monjalon <tho...@monjalon.net> > > > > Cc: Jerin Jacob <jer...@marvell.com>; dpdk-dev <dev@dpdk.org>; > > > > Stephen > > > Hemminger > > > > <step...@networkplumber.org>; David Marchand > > > <david.march...@redhat.com>; Andrew Rybchenko > > > > <andrew.rybche...@oktetlabs.ru>; Wang, Haiyue > > > > <haiyue.w...@intel.com>; > > > Honnappa Nagarahalli > > > > <honnappa.nagaraha...@arm.com>; Yigit, Ferruh > > > > <ferruh.yi...@intel.com>; > > > techbo...@dpdk.org; Elena > > > > Agostini <eagost...@nvidia.com> > > > > Subject: Re: [dpdk-dev] [RFC PATCH v2 0/7] heterogeneous computing > > > > library > > > > > > > > On Fri, Aug 27, 2021 at 3:14 PM Thomas Monjalon > > > > <tho...@monjalon.net> > > > wrote: > > > > > > > > > > 31/07/2021 15:42, Jerin Jacob: > > > > > > On Sat, Jul 31, 2021 at 1:51 PM Thomas Monjalon > > > <tho...@monjalon.net> wrote: > > > > > > > 31/07/2021 09:06, Jerin Jacob: > > > > > > > > On Fri, Jul 30, 2021 at 7:25 PM Thomas Monjalon > > > <tho...@monjalon.net> wrote: > > > > > > > > > From: Elena Agostini <eagost...@nvidia.com> > > > > > > > > > > > > > > > > > > In heterogeneous computing system, processing is not > > > > > > > > > only in the > > > CPU. > > > > > > > > > Some tasks can be delegated to devices working in parallel. > > > > > > > > > > > > > > > > > > The goal of this new library is to enhance the > > > > > > > > > collaboration between DPDK, that's primarily a CPU > > > > > > > > > framework, and other type of devices > > > like GPUs. > > > > > > > > > > > > > > > > > > When mixing network activity with task processing on a > > > > > > > > > non-CPU > > > device, > > > > > > > > > there may be the need to put in communication the CPU > > > > > > > > > with the > > > device > > > > > > > > > in order to manage the memory, synchronize operations, > > > > > > > > > exchange > > > info, etc.. > > > > > > > > > > > > > > > > > > This library provides a number of new features: > > > > > > > > > - Interoperability with device specific library with > > > > > > > > > generic handlers > > > > > > > > > - Possibility to allocate and free memory on the device > > > > > > > > > - Possibility to allocate and free memory on the CPU but > > > > > > > > > visible from > > > the device > > > > > > > > > - Communication functions to enhance the dialog between > > > > > > > > > the CPU > > > and the device > > > > > > > > > > > > > > > > > > The infrastructure is prepared to welcome drivers in > > > > > > > > > drivers/hc/ as the upcoming NVIDIA one, implementing the > hcdev API. > > > > > > > > > > > > > > > > > > Some parts are not complete: > > > > > > > > > - locks > > > > > > > > > - memory allocation table > > > > > > > > > - memory freeing > > > > > > > > > - guide documentation > > > > > > > > > - integration in devtools/check-doc-vs-code.sh > > > > > > > > > - unit tests > > > > > > > > > - integration in testpmd to enable Rx/Tx to/from GPU > memory. > > > > > > > > > > > > > > > > Since the above line is the crux of the following text, I > > > > > > > > will start from this point. > > > > > > > > > > > > > > > > + Techboard > > > > > > > > > > > > > > > > I can give my honest feedback on this. > > > > > > > > > > > > > > > > I can map similar stuff in Marvell HW, where we do > > > > > > > > machine learning as compute offload on a different class > > > > > > > > of CPU. > > > > > > > > > > > > > > > > In terms of RFC patch features > > > > > > > > > > > > > > > > 1) memory API - Use cases are aligned > > > > > > > > 2) communication flag and communication list Our structure > > > > > > > > is completely different and we are using HW ring kind of > > > > > > > > interface to post the job to compute interface and the job > > > > > > > > completion result happens through the event device. > > > > > > > > Kind of similar to the DMA API that has been discussed on > > > > > > > > the mailing > > > list. > > > > > > > > > > > > > > Interesting. > > > > > > > > > > > > It is hard to generalize the communication mechanism. > > > > > > Is other GPU vendors have a similar communication mechanism? > > > > > > AMD, > > > Intel ?? > > > > > > > > > > I don't know who to ask in AMD & Intel. Any ideas? > > > > > > > > Good question. > > > > > > > > At least in Marvell HW, the communication flag and communication > > > > list is our structure is completely different and we are using HW > > > > ring kind of interface to post the job to compute interface and > > > > the job completion result happens through the event device. > > > > kind of similar to the DMA API that has been discussed on the mailing > list. > > > > Please correct me if I'm wrong but what you are describing is a > > specific way to submit work on the device. Communication flag/list > > here is a direct data communication between the CPU and some kind of > > workload (e.g. GPU kernel) that's already running on the device. > > Exactly. What I meant is Communication flag/list is not generic enough to > express and generic compute device. If all GPU works in this way, we could > make the library name as GPU specific and add GPU specific communication > mechanism.
I'm in favor of reverting the name of the library with a more specific gpudev name instead of hcdev. This library (both memory allocations and fancy features like communication lists) can be tested on various GPUs but I'm not sure about other type of devices. Again, as initial step, I would not complicate things Let's have a GPU oriented library for now. > > > > > > The rationale here is that: > > - some work has been already submitted on the device and it's running > > - CPU needs a real-time direct interaction through memory with the > > device > > - the workload on the device needs some info from the CPU it can't get > > at submission time > > > > This is good enough for NVIDIA and AMD GPU. > > Need to double check for Intel GPU. > > > > > > > > > > > > > > > > > > > Now the bigger question is why need to Tx and then Rx > > > > > > > > something to compute the device Isn't ot offload > > > > > > > > something? If so, why not add the those offload in > > > > > > > > respective subsystem to improve the subsystem(ethdev, > > > > > > > > cryptiodev etc) features set to adapt new features or > > > > > > > > introduce new subsystem (like ML, Inline Baseband > > > > > > > > processing) so that it will be an opportunity to implement > > > > > > > > the same in HW or compute device. For example, if we take > > > > > > > > this path, ML offloading will be application code like > > > > > > > > testpmd, which deals with "specific" device commands(aka > > > > > > > > glorified rawdev) to deal with specific computing device > > > > > > > > offload "COMMANDS" > > > > > > > > (The commands will be specific to offload device, the > > > > > > > > same code wont run on other compute device) > > > > > > > > > > > > > > Having specific features API is convenient for compatibility > > > > > > > between devices, yes, for the set of defined features. > > > > > > > Our approach is to start with a flexible API that the > > > > > > > application can use to implement any processing because with > > > > > > > GPU programming, there is no restriction on what can be > achieved. > > > > > > > This approach does not contradict what you propose, it does > > > > > > > not prevent extending existing classes. > > > > > > > > > > > > It does prevent extending the existing classes as no one is > > > > > > going to extent it there is the path of not doing do. > > > > > > > > > > I disagree. Specific API is more convenient for some tasks, so > > > > > there is an incentive to define or extend specific device class APIs. > > > > > But it should not forbid doing custom processing. > > > > > > > > This is the same as the raw device is in DPDK where the device > > > > personality is not defined. > > > > > > > > Even if define another API and if the personality is not defined, > > > > it comes similar to the raw device as similar to rawdev enqueue > > > > and dequeue. > > > > > > > > To summarize, > > > > > > > > 1) My _personal_ preference is to have specific subsystems to > > > > improve the DPDK instead of the raw device kind of path. > > > > > > Something like rte_memdev to focus on device (GPU) memory > management ? > > > > > > The new DPDK auxiliary bus maybe make life easier to solve the > > > complex heterogeneous computing library. ;-) > > > > To get a concrete idea about what's the best and most comprehensive > > approach we should start with something that's flexible and simple > enough. > > > > A dedicated library it's a good starting point: easy to implement and > > embed in DPDK applications, isolated from other components and users > can play with it learning from the code. > > As a second step we can think to embed the functionality in some other > > way within DPDK (e.g. split memory management and communication > features). > > > > > > > > > 2) If the device personality is not defined, use rawdev > > > > 3) All computing devices do not use "communication flag" and > > > > "communication list" > > > > kind of structure. If are targeting a generic computing device > > > > then that is not a portable scheme. > > > > For GPU abstraction if "communication flag" and "communication > list" > > > > is the right kind of mechanism > > > > then we can have a separate library for GPU communication specific > > > > to GPU <- > > > > > > > > DPDK communication needs and explicit for GPU. > > > > > > > > I think generic DPDK applications like testpmd should not pollute > > > > with device-specific functions. Like, call device-specific > > > > messages from the application which makes the application runs > > > > only one device. I don't have a strong opinion(expect > > > > standardizing "communication flag" and "communication list" as > > > > generic computing device communication mechanism) of others think > > > > it is OK to do that way in DPDK. > > > > I'd like to introduce (with a dedicated option) the memory API in > > testpmd to provide an example of how to TX/RX packets using device > memory. > > Not sure without embedding sideband communication mechanism how it > can notify to GPU and back to CPU. If you could share the example API > sequence that helps to us understand the level of coupling with testpmd. > There is no need of communication mechanism here. Assuming there is not workload to process network packets (to not complicate things), the steps are: 1) Create a DPDK mempool with device external memory using the hcdev (or gpudev) library 2) Use that mempool to tx/rx/fwd packets As an example, you look at my l2fwd-nv application here: https://github.com/NVIDIA/l2fwd-nv > > > > > I agree to not embed communication flag/list features. > > > > > > > > > > > > > > > > > If an application can run only on a specific device, it is > > > > > > similar to a raw device, where the device definition is not > > > > > > defined. (i.e JOB metadata is not defined > > > and > > > > > > it is specific to the device). > > > > > > > > > > > > > > Just my _personal_ preference is to have specific > > > > > > > > subsystems to improve the DPDK instead of raw device kind > > > > > > > > of path. If we decide another path as a community it is > > > > > > > > _fine_ too(as a _project manager_ point of view it will be > > > > > > > > an easy path to dump SDK stuff to DPDK without introducing > > > > > > > > the pain of the subsystem nor improving the DPDK). > > > > > > > > > > > > > > Adding a new class API is also improving DPDK. > > > > > > > > > > > > But the class is similar as raw dev class. The reason I say, > > > > > > Job submission and response is can be abstracted as > queue/dequeue APIs. > > > > > > Taks/Job metadata is specific to compute devices (and it can > > > > > > not be generalized). > > > > > > If we generalize it makes sense to have a new class that does > > > > > > "specific function". > > > > > > > > > > Computing device programming is already generalized with > > > > > languages like > > > OpenCL. > > > > > We should not try to reinvent the same. > > > > > We are just trying to properly integrate the concept in DPDK and > > > > > allow building on top of it. > > > > Agree. > > > > > > > > > > See above. > > > > > > > > > > > > > >
