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* gpu: nvgpu: Give nvgpu_kalloc a less generic nameAlex Waterman2017-03-03
| | | | | | | | | | | | | | | | | | | | | | Change nvgpu_kalloc() to nvgpu_big_[mz]alloc(). This is necessary since the natural free function name for this is nvgpu_kfree() but that conflicts with nvgpu_k[mz]alloc() (implemented in a subsequent patch). This API exists becasue not all allocation sizes can be determined at compile time and in some cases sizes may vary across the system page size. Thus always using kmalloc() could lead to OOM errors due to fragmentation. But always using vmalloc() is wastful of memory for small allocations. This API tries to alleviate those problems. Bug 1799159 Bug 1823380 Change-Id: I49ec5292ce13bcdecf112afbb4a0cfffeeb5ecfc Signed-off-by: Alex Waterman <alexw@nvidia.com> Reviewed-on: http://git-master/r/1283827 Reviewed-by: mobile promotions <svcmobile_promotions@nvidia.com> Tested-by: mobile promotions <svcmobile_promotions@nvidia.com>
* gpu: nvgpu: remove use of DEFINE_MUTEX()Deepak Nibade2017-02-22
| | | | | | | | | | | | | | | | | | | API DEFINE_MUTEX() is defined in Linux and might not be available in other OSs. Hence remove its usage from nvgpu Declare and explicitly initialize below mutexes for both nvgpu and vgpu g->mm.priv_lock g->mm.tlb_lock Jira NVGPU-13 Change-Id: If72885a6da0227a1552303206172f1f2b751471d Signed-off-by: Deepak Nibade <dnibade@nvidia.com> Reviewed-on: http://git-master/r/1298042 Reviewed-by: mobile promotions <svcmobile_promotions@nvidia.com> Tested-by: mobile promotions <svcmobile_promotions@nvidia.com>
* gpu: nvgpu: use common nvgpu mutex/spinlock APIsDeepak Nibade2017-02-22
| | | | | | | | | | | | | | | | | | | | | | | | | | | Instead of using Linux APIs for mutex and spinlocks directly, use new APIs defined in <nvgpu/lock.h> Replace Linux specific mutex/spinlock declaration, init, lock, unlock APIs with new APIs e.g struct mutex is replaced by struct nvgpu_mutex and mutex_lock() is replaced by nvgpu_mutex_acquire() And also include <nvgpu/lock.h> instead of including <linux/mutex.h> and <linux/spinlock.h> Add explicit nvgpu/lock.h includes to below files to fix complilation failures. gk20a/platform_gk20a.h include/nvgpu/allocator.h Jira NVGPU-13 Change-Id: I81a05d21ecdbd90c2076a9f0aefd0e40b215bd33 Signed-off-by: Deepak Nibade <dnibade@nvidia.com> Reviewed-on: http://git-master/r/1293187 Reviewed-by: mobile promotions <svcmobile_promotions@nvidia.com> Tested-by: mobile promotions <svcmobile_promotions@nvidia.com>
* gpu: nvgpu: Move from gk20a_ to nvgpu_ in semaphore codeAlex Waterman2017-02-13
| | | | | | | | | | | | | Change the prefix in the semaphore code to 'nvgpu_' since this code is global to all chips. Bug 1799159 Change-Id: Ic1f3e13428882019e5d1f547acfe95271cc10da5 Signed-off-by: Alex Waterman <alexw@nvidia.com> Reviewed-on: http://git-master/r/1284628 Reviewed-by: Varun Colbert <vcolbert@nvidia.com> Tested-by: Varun Colbert <vcolbert@nvidia.com>
* gpu: nvgpu: Organize semaphore_gk20a.[ch]Alex Waterman2017-02-13
| | | | | | | | | | | | | | | | | | | | | | | Move semaphore_gk20a.c drivers/gpu/nvgpu/common/ since the semaphore code is common to all chips. Move the semaphore_gk20a.h header file to drivers/gpu/nvgpu/include/nvgpu and rename it to semaphore.h. Also update all places where the header is inluced to use the new path. This revealed an odd location for the enum gk20a_mem_rw_flag. This should be in the mm headers. As a result many places that did not need anything semaphore related had to include the semaphore header file. Fixing this oddity allowed the semaphore include to be removed from many C files that did not need it. Bug 1799159 Change-Id: Ie017219acf34c4c481747323b9f3ac33e76e064c Signed-off-by: Alex Waterman <alexw@nvidia.com> Reviewed-on: http://git-master/r/1284627 GVS: Gerrit_Virtual_Submit Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: Simplify ref-counting on VMsAlex Waterman2017-02-07
| | | | | | | | | | | | | | | | | | | | Simplify ref-counting on VMs: take a ref when a VM is bound to a channel and drop a ref when a channel is freed. Previously ref-counts were scattered over the driver. Also the CE and CDE code would bind channels with custom rolled code. This was because the gk20a_vm_bind_channel() function took an as_share as the VM argument (the VM was then inferred from that as_share). However, it is trivial to abtract that bit out and allow a central bind channel function that just takes a VM and a channel. Bug 1846718 Change-Id: I156aab259f6c7a2fa338408c6c4a3a464cd44a0c Signed-off-by: Alex Waterman <alexw@nvidia.com> Reviewed-on: http://git-master/r/1261886 Reviewed-by: Richard Zhao <rizhao@nvidia.com> Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: Conditional address space unificationAlex Waterman2017-01-31
| | | | | | | | | | | | | | | | Allow platforms to choose whether or not to have unified GPU VA spaces. This is useful for the dGPU where having a unified address space has no problems. On iGPUs testing issues is getting in the way of enabling this feature. Bug 1396644 Bug 1729947 Change-Id: I65985f1f9a818f4b06219715cc09619911e4824b Signed-off-by: Alex Waterman <alexw@nvidia.com> Reviewed-on: http://git-master/r/1265303 GVS: Gerrit_Virtual_Submit Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: Remove separate fixed address VMAAlex Waterman2017-01-31
| | | | | | | | | | | | | | Remove the special VMA that could be used for allocating fixed addresses. This feature was never used and is not worth maintaining. Bug 1396644 Bug 1729947 Change-Id: I06f92caa01623535516935acc03ce38dbdb0e318 Signed-off-by: Alex Waterman <alexw@nvidia.com> Reviewed-on: http://git-master/r/1265302 GVS: Gerrit_Virtual_Submit Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: Unify the small and large page address spacesAlex Waterman2017-01-31
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | The basic structure of this patch is to make the small page allocator and the large page allocator into pointers (where they used to be just structs). Then assign each of those pointers to the same actual allocator since the buddy allocator has supported mixed page sizes since its inception. For the rest of the driver some changes had to be made in order to actually support mixed pages in a single address space. 1. Unifying the allocation page size determination Since the allocation and map operations happen at distinct times both mapping and allocation of GVA space must agree on page size. This is because the allocation has to separate allocations into separate PDEs to avoid the necessity of supporting mixed PDEs. To this end a function __get_pte_size() was introduced which is used both by the balloc code and the core GPU MM code. It determines page size based only on the length of the mapping/ allocation. 2. Fixed address allocation + page size Similar to regular mappings/GVA allocations fixed address mapping page size determination had to be modified. In the past the address of the mapping determined page size since the address space split was by address (low addresses were small pages, high addresses large pages). Since that is no longer the case the page size field in the reserve memory ioctl is now honored by the mapping code. When, for instance, CUDA makes a memory reservation it specifies small or large pages. When CUDA requests mappings to be made within that address range the page size is then looked up in the reserved memory struct. Fixed address reservations were also modified to now always allocate at a PDE granularity (64M or 128M depending on large page size. This prevents non-fixed allocations from ending up in the same PDE and causing kernel panics or GMMU faults. 3. The rest... The rest of the changes are just by products of the above. Lots of places required minor updates to use a pointer to the GVA allocator struct instead of the struct itself. Lastly, this change is not truly complete. More work remains to be done in order to fully remove the notion that there was such a thing as separate address spaces for different page sizes. Basically after this patch what remains is cleanup and proper documentation. Bug 1396644 Bug 1729947 Change-Id: If51ab396a37ba16c69e434adb47edeef083dce57 Signed-off-by: Alex Waterman <alexw@nvidia.com> Reviewed-on: http://git-master/r/1265300 GVS: Gerrit_Virtual_Submit Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: Remove circular dependency in PMU includesTerje Bergstrom2017-01-27
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | Remove including gk20a.h from pmu_gk20a.h. This causes a fallout as some #includes were missing. gr_gp10b.h uses mem_desc, but did not include mm_gk20a.h. Add the include. Including mm_gk20a.h in gr_gp10b.h causes recursive include, as mm_gk20a.h has some gr defines. Move the defines to gr_gk20a.h to remove the dependency. gr_ctx_gk20a.h used struct gk20a pointers, but did not forward declare it. Add a forward declaration. gr_gk20a.h uses dbg_session_gk20a, but was missing forward declaration. gr_gk20a.h did not include nvgpu.h but it uses preemption types from that header. Add include. Change-Id: I2168e2303b55e0d187b816bcb26f37c8af1649ba Signed-off-by: Terje Bergstrom <tbergstrom@nvidia.com> Reviewed-on: http://git-master/r/1283717 Reviewed-by: Alex Waterman <alexw@nvidia.com> Reviewed-by: svccoveritychecker <svccoveritychecker@nvidia.com> GVS: Gerrit_Virtual_Submit Reviewed-by: Seshendra Gadagottu <sgadagottu@nvidia.com>
* gpu: nvgpu: use soc/tegra/chip-id.h for soc headerShardar Shariff Md2017-01-20
| | | | | | | | | | | | The soc tegra headers are unified and moved all the content of linux/tegra-soc.h to the soc/tegra/chip-id.h to have the single soc header for Tegra. Change-Id: I281e19dd3eb1538b8dfbea4eb0779fb64d1fcffa Signed-off-by: Shardar Shariff Md <smohammed@nvidia.com> Reviewed-on: http://git-master/r/1288365 Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com> Tested-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: Move allocators to common/mm/Alex Waterman2017-01-09
| | | | | | | | | | | | | | | | | | | Move the GPU allocators to common/mm/ since the allocators are common code across all GPUs. Also rename the allocator code to move away from gk20a_ prefixed structs and functions. This caused one issue with the nvgpu_alloc() and nvgpu_free() functions. There was a function for allocating either with kmalloc() or vmalloc() depending on the size of the allocation. Those have now been renamed to nvgpu_kalloc() and nvgpu_kfree(). Bug 1799159 Change-Id: Iddda92c013612bcb209847084ec85b8953002fa5 Signed-off-by: Alex Waterman <alexw@nvidia.com> Reviewed-on: http://git-master/r/1274400 Reviewed-by: mobile promotions <svcmobile_promotions@nvidia.com> Tested-by: mobile promotions <svcmobile_promotions@nvidia.com>
* gpu: nvgpu: make preemption modes unsignedDeepak Nibade2016-12-21
| | | | | | | | | | | | | | | | | | | | graphics and compute preemption modes are currently defined as int But it is more logical to have them as unsigned int Also, we treat preemption modes as unsigned almost everywhere in the code Fix prints in gk20a_fifo_sched_debugfs_seq_show() to print U32_MAX with %d which is same as printing -1 Bug 200263471 Change-Id: Iabd0ee3923b76d81620898e90a9b1fc5dd75b530 Signed-off-by: Deepak Nibade <dnibade@nvidia.com> Reviewed-on: http://git-master/r/1272514 Reviewed-by: mobile promotions <svcmobile_promotions@nvidia.com> Tested-by: mobile promotions <svcmobile_promotions@nvidia.com>
* gpu: nvgpu: copy data into channel context headerseshendra Gadagottu2016-12-20
| | | | | | | | | | | | | | If channel context has separate context header then copy required info into context header instead of main context header. JIRA GV11B-21 Change-Id: I5e0bdde132fb83956fd6ac473148ad4de498e830 Signed-off-by: seshendra Gadagottu <sgadagottu@nvidia.com> Reviewed-on: http://git-master/r/1229243 Reviewed-by: mobile promotions <svcmobile_promotions@nvidia.com> Tested-by: mobile promotions <svcmobile_promotions@nvidia.com>
* gpu: nvgpu: Use end of vidmem as bootstrap regionTerje Bergstrom2016-12-09
| | | | | | | | | | | | | | | | | Instead of hard coding bootstrap region, it should always be set to the last 256MB of vidmem. Bug 200244445 Change-Id: I91779d1bf861f4f23a0b646f70b1febbbc4581b5 Signed-off-by: David Nieto <dmartineznie@nvidia.com> Reviewed-on: http://git-master/r/1242409 Reviewed-by: David Martinez Nieto <dmartineznie@nvidia.com> Reviewed-by: Alex Waterman <alexw@nvidia.com> GVS: Gerrit_Virtual_Submit Reviewed-on: http://git-master/r/1267124 Reviewed-by: mobile promotions <svcmobile_promotions@nvidia.com> Tested-by: mobile promotions <svcmobile_promotions@nvidia.com>
* gpu: nvgpu: API to access fb memoryDeepak Nibade2016-11-30
| | | | | | | | | | | | | | | | | | | | | | | | | | | | Add IOCTL API NVGPU_DBG_GPU_IOCTL_ACCESS_FB_MEMORY to read/write fb/vidmem memory Interface will accept dmabuf_fd of the buffer in vidmem, offset into the buffer to access, temporary buffer to copy data across API, size of read/write and command indicating either read or write operation API will first parse all the inputs, and then call gk20a_vidbuf_access_memory() to complete fb access gk20a_vidbuf_access_memory() will then just use gk20a_mem_rd_n() or gk20a_mem_wr_n() depending on the command issued Bug 1804714 Jira DNVGPU-192 Change-Id: Iba3c42410abe12c2884d3b603fa33d27782e4c56 Signed-off-by: Deepak Nibade <dnibade@nvidia.com> Reviewed-on: http://git-master/r/1255556 (cherry picked from commit 2c49a8a79d93fc526adbf6f808484fa9a3fa2498) Reviewed-on: http://git-master/r/1260471 GVS: Gerrit_Virtual_Submit Reviewed-by: Bharat Nihalani <bnihalani@nvidia.com>
* Revert "Revert "gpu: nvgpu: vgpu: alloc hwpm ctxt buf on client""Peter Daifuku2016-11-14
| | | | | | | | | | | | | | | | | This reverts commit 5f1c2bc27fb9dd66ed046b0590afc365be5011bf. Added back now that matching RM server has been updated: In hypervisor mode, all GPU VA allocations must be done by client; fix this for the allocation of the hwpm ctxt buffer Bug 200231611 Change-Id: Ie5ce2c2562401b1f00821231d37608e3fc30d4a4 Signed-off-by: Peter Daifuku <pdaifuku@nvidia.com> Reviewed-on: http://git-master/r/1252138 GVS: Gerrit_Virtual_Submit Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com>
* Revert "gpu: nvgpu: vgpu: alloc hwpm ctxt buf on client"Sivaram Nair2016-11-04
| | | | | | | | | | This reverts commit 57821e215756b3df7acc9c0eb5017e39f141d381. Change-Id: Ic4801115064ccbcd1435298a61871921d056b8ea Signed-off-by: Sivaram Nair <sivaramn@nvidia.com> Reviewed-on: http://git-master/r/1247825 Reviewed-by: Rakesh Babu Bodla <rbodla@nvidia.com> Tested-by: Rakesh Babu Bodla <rbodla@nvidia.com>
* gpu: nvgpu: vgpu: alloc hwpm ctxt buf on clientPeter Daifuku2016-11-03
| | | | | | | | | | | | | | | | | | In hypervisor mode, all GPU VA allocations must be done by client; fix this for the allocation of the hwpm ctxt buffer Bug 200231611 Change-Id: I0270b1298308383a969a47d0a859ed53c20594ef Signed-off-by: Peter Daifuku <pdaifuku@nvidia.com> Reviewed-on: http://git-master/r/1240913 (cherry picked from commit 49314d42b13e27dc2f8c1e569a8c3e750173148d) Reviewed-on: http://git-master/r/1245867 (cherry picked from commit d0b10e84d90d0fd61eca8be0f9e879d9cec71d3e) Reviewed-on: http://git-master/r/1246700 Reviewed-by: Automatic_Commit_Validation_User GVS: Gerrit_Virtual_Submit Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: Move CE cleanupAlex Waterman2016-10-26
| | | | | | | | | | | | | | | | Move the CE cleanup to before the FIFO cleanup. Since the CE closes a channel during its cleanup the FIFO needs to be initialized since the FIFO code maintains the vmalloc()'ed channels. Bug 1816516 Change-Id: Ia7a97059a12a0c2b52368ffe411e597f803e8e6e Signed-off-by: Alex Waterman <alexw@nvidia.com> Reviewed-on: http://git-master/r/1225613 (cherry picked from commit 707bd2a6d4672c6a7b7a8b2e581ea3a606ed971d) Reviewed-on: http://git-master/r/1240106 GVS: Gerrit_Virtual_Submit Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: use inplace allocation in sync frameworkSachit Kadle2016-10-20
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This change is the first of a series of changes to support the usage of pre-allocated job tracking resources in the submit path. With this change, we still maintain a dynamically-allocated joblist, but make the necessary changes in the channel_sync & fence framework to use in-place allocations. Specifically, we: 1) Update channel sync framework routines to take in pre-allocated priv_cmd_entry(s) & gk20a_fence(s) rather than dynamically allocating themselves 2) Move allocation of priv_cmd_entry(s) & gk20a_fence(s) to gk20a_submit_prepare_syncs 3) Modify fence framework to have seperate allocation and init APIs. We expose allocation as a seperate API, so the client can allocate the object before passing it into the channel sync framework. 4) Fix clean_up logic in channel sync framework Bug 1795076 Change-Id: I96db457683cd207fd029c31c45f548f98055e844 Signed-off-by: Sachit Kadle <skadle@nvidia.com> Reviewed-on: http://git-master/r/1206725 (cherry picked from commit 9d196fd10db6c2f934c2a53b1fc0500eb4626624) Reviewed-on: http://git-master/r/1223933 Reviewed-by: mobile promotions <svcmobile_promotions@nvidia.com> Tested-by: mobile promotions <svcmobile_promotions@nvidia.com>
* gpu: nvgpu: allow skipping pramin barriersKonsta Holtta2016-10-17
| | | | | | | | | | | | | | | | | | | | | A wmb() next to each gk20a_mem_wr32() via PRAMIN may be overly careful, so support not inserting these barriers for performance, in cases where they are not necessary, where the caller would do an explicit barrier after a bunch of reads. Also, move those optional wmb()s to be done at the end of the whole internally batched write for gk20a_mem_{wr_n,memset} from the per-batch subloops that may run multiple times. Jira DNVGPU-23 Change-Id: I61ee65418335863110bca6f036b2e883b048c5c2 Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1225149 (cherry picked from commit d2c40327d1995f76e8ab9cb4cd8c76407dabc6de) Reviewed-on: http://git-master/r/1227474 Reviewed-by: mobile promotions <svcmobile_promotions@nvidia.com> Tested-by: mobile promotions <svcmobile_promotions@nvidia.com>
* gpu: nvgpu: add ioctl for querying memory stateKonsta Holtta2016-10-14
| | | | | | | | | | | | | | | | | | | Add NVGPU_GPU_IOCTL_GET_MEMORY_STATE to read the amount of free device-local video memory, if applicable. Some reserved fields are added to support different types of queries in the future (e.g. context-local free amount). Bug 1787771 Bug 200233138 Change-Id: Id5ffd02ad4d6ed3a6dc196541938573c27b340ac Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1223762 (cherry picked from commit 96221d96c7972c6387944603e974f7639d6dbe70) Reviewed-on: http://git-master/r/1235980 Reviewed-by: mobile promotions <svcmobile_promotions@nvidia.com> Tested-by: mobile promotions <svcmobile_promotions@nvidia.com>
* gpu: nvgpu: track pending bytes for vidmem clearsKonsta Holtta2016-10-14
| | | | | | | | | | | | | | | | | Change clears_pending to bytes_pending and track accordingly the number of bytes to be freed instead of the number of buffers. This, atomically combined with the amount of space in the allocator, is the total amount of free memory available. Bug 200233138 Change-Id: Ibbb4e80a32728781ba19a74307d8a8ac1a4d7431 Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1231422 (cherry picked from commit 025e765f312c253b201ecf2dbbe0f4972fe1d4bc) Reviewed-on: http://git-master/r/1235957 Reviewed-by: mobile promotions <svcmobile_promotions@nvidia.com> Tested-by: mobile promotions <svcmobile_promotions@nvidia.com>
* gpu: nvgpu: mark vidmem.cleared volatileKonsta Holtta2016-10-14
| | | | | | | | | | | | | | | | The boolean flag mm_gk20a.vidmem.cleared is shared across threads, so mark it volatile to prevent compiler from wrongly optimizing accesses to it. Jira DNVGPU-84 Change-Id: I1fe66b26966685d3f74ed95ba53b198f810231b9 Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1233016 (cherry picked from commit dc6c9db56ea8a5f55f28f97fdfc3c1ac60d8b195) Reviewed-on: http://git-master/r/1235317 Reviewed-by: mobile promotions <svcmobile_promotions@nvidia.com> Tested-by: mobile promotions <svcmobile_promotions@nvidia.com>
* gpu: nvgpu: compact pte buffersKonsta Holtta2016-10-13
| | | | | | | | | | | | | | | | | | | | | | The lowest page table level may hold very few entries for mappings of large pages, but a new page is allocated for each list of entries at the lowest level, wasting memory and performance. Compact these so that the new "allocation" of ptes is appended at the end of the previous allocation, if there is space. 4 KB page is still the smallest size requested from the allocator; any possible overhead in the allocator (e.g., internally allocating big pages only) is not taken into account. Bug 1736604 Change-Id: I03fb795cbc06c869fcf5f1b92def89a04583ee83 Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1221841 (cherry picked from commit fa92017ed48e1d5f48c1a12c512641c6ce9924af) Reviewed-on: http://git-master/r/1234996 Reviewed-by: mobile promotions <svcmobile_promotions@nvidia.com> Tested-by: mobile promotions <svcmobile_promotions@nvidia.com>
* gpu: nvgpu: make sure vidmem is cleared only onceKonsta Holtta2016-10-12
| | | | | | | | | | | | | | | | | | Protect the initial vidmem zeroing performed during the first userspace alloc with a mutex, so that it blocks next concurrent users and is run only once. Otherwise, multiple clears could end up running in parallel, so that the next ones corrupt memory allocated by the thread that has finished earlier and advanced to allocate and use memory. Jira DNVGPU-84 Change-Id: If497749abf481b230835250191d011c4a9d1483b Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1232461 (cherry picked from commit 79435a68e6d2713b78acdb0ec6f77cfd78651d7f) Reviewed-on: http://git-master/r/1234990 GVS: Gerrit_Virtual_Submit Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: test free user vidmem atomicallyKonsta Holtta2016-09-14
| | | | | | | | | | | | | | | | | | | | | | | | | | | An empty list of soon-to-be-freed userspace vidmem buffers is not enough to safely assume that an allocation may succeed or not if tried again, because removal from the list and actually marking the memory freed is not atomic. Fix this by using an atomic counter for the number of pending frees (so that it's still safe to first remove from the job list and then perform the free), and making allocation attempts combined with a test of pending frees atomic. This still does not guarantee that there is memory available (as the actual amount of pending memory in bytes plus the current free amount isn't computed), but removes the race that produces false negatives in case a single program expects repeated frees and allocs to succeed. Bug 1809939 Change-Id: I6a92da2e21cbf3f886b727000c924d56f35ce55b Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1217078 (cherry picked from commit 83c1f1e70dccd92fdd4481132cf5b6717760d432) Reviewed-on: http://git-master/r/1220545 Reviewed-by: Automatic_Commit_Validation_User GVS: Gerrit_Virtual_Submit Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com> Tested-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: add new API to get base address for sysmem/vidmem buffersDeepak Nibade2016-09-01
| | | | | | | | | | | | | | | | | | | | | | | Add new API gk20a_mem_get_base_addr() which will return vidmem base address in case of vidmem and IOVA address in case of sysmem Even though vidmem allocations are non-contiguous, this API is useful (and should only be used) for allocations with one chunk (e.g. page tables) Also, since page tables could either reside in sysmem or vidmem, use this API to get address of page tables Jira DNVGPU-20 Change-Id: Ie04af9ca7bfccfec1a8a8e4be2c507cef5cef8e1 Signed-off-by: Deepak Nibade <dnibade@nvidia.com> Reviewed-on: http://git-master/r/1206403 (cherry picked from commit a8c74dc188878f2948fa1e0e47bf1837fba6c5e0) Reviewed-on: http://git-master/r/1210957 Reviewed-by: mobile promotions <svcmobile_promotions@nvidia.com> Tested-by: mobile promotions <svcmobile_promotions@nvidia.com>
* gpu: nvgpu: track allocator and user for each memDeepak Nibade2016-09-01
| | | | | | | | | | | | | | | | | | | | | | | | | Store allocator pointer for each mem_desc This pointer should be used while freeing the mem instead of assuming a common allocator Add flag user_mem to mem_desc which will be set only in case of User vidmem allocations We will delay free of mem in worker only if this flag is set on mem. Otherwise, we will free it immediately This is needed so that all kernel allocations can work with both sysmem and vidmem Jira DNVGPU-84 Change-Id: Ib9a9209b164bc56b7880448f86bd6d42b324cc86 Signed-off-by: Deepak Nibade <dnibade@nvidia.com> Reviewed-on: http://git-master/r/1203099 (cherry picked from commit 8f0b0122f36a0b6f1932fa9a98d7eb03b1f623d1) Reviewed-on: http://git-master/r/1210953 Reviewed-by: mobile promotions <svcmobile_promotions@nvidia.com> Tested-by: mobile promotions <svcmobile_promotions@nvidia.com>
* gpu: nvgpu: clear vidmem buffers in workerDeepak Nibade2016-09-01
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | We clear buffers allocated in vidmem in buffer free path. But to clear buffers, we need to submit CE jobs and this could cause issues/races if free called from critical path Hence solve this by moving buffer clear/free to a worker gk20a_gmmu_free_attr_vid() will now just put mem_desc into a list and schedule a worker And worker thread will traverse the list and clear/free the allocations In struct gk20a_vidmem_buf, mem variable is statically allocated. But since we delay free of mem, convert this variable into a pointer and allocate it dynamically Since we delay free of vidmem memory, it is now possible to face OOM conditions during allocations. Hence while allocating block until we have sufficient memory available with an upper limit of 1S Jira DNVGPU-84 Change-Id: I7925590644afae50b6fc04c6e1e43bbaa1c220fd Signed-off-by: Deepak Nibade <dnibade@nvidia.com> Reviewed-on: http://git-master/r/1201346 (cherry picked from commit b4dec4a30de2431369d677acca00e420f8e581a5) Reviewed-on: http://git-master/r/1210950 Reviewed-by: mobile promotions <svcmobile_promotions@nvidia.com> Tested-by: mobile promotions <svcmobile_promotions@nvidia.com>
* gpu: nvgpu: clear whole vidmem on first allocationDeepak Nibade2016-09-01
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | We currently clear vidmem pages in gk20a_gmmu_alloc_attr_vid_at() i.e. allocation path for each buffer But since buffer allocation path could be latency critical, clear whole vidmem first and before first User allcation in gk20a_vidmem_buf_alloc() And then clear buffer pages while releasing the buffer In this way, we can ensure that vidmem pages are already cleared during buffer allocation path At a later stage, clearing of pages can be removed from free path and moved to a separate worker as well At this point, first allocation has overhead of clearing whole vidmem which takes about 380mS and this should improve once clocks are raised. Also, this is one time larency, and subsequent allocations should not have any overhead for clearing at all Add API gk20a_vidmem_clear_all() to clear whole vidmem We have WPR buffers allocated during boot up and at fixed address in vidmem. To prevent overwriting to these buffers in gk20a_vidmem_clear_all(), clear whole vidmem except for the bootstrap allocator carveout Add new API gk20a_gmmu_clear_vidmem_mem() to clear one mem_desc Jira DNVGPU-84 Change-Id: I5661700585c6241a6a1ddeb5b7c068d3d2aed4b3 Signed-off-by: Deepak Nibade <dnibade@nvidia.com> Reviewed-on: http://git-master/r/1194301 (cherry picked from commit 950ab61a04290ea405968d8b0d03e3bd044ce83d) Reviewed-on: http://git-master/r/1193158 Reviewed-by: mobile promotions <svcmobile_promotions@nvidia.com> Tested-by: mobile promotions <svcmobile_promotions@nvidia.com>
* gpu: nvgpu: Add a bootstrap vidmem allocatorAlex Waterman2016-09-01
| | | | | | | | | | | | | | | | Add an allocator for allocating vidmem before the CE has had a chance to be initialized (and clear the rest of vidmem). Jira DNVGPU-84 Change-Id: I5166607a712b3a6eb4c2906b8c7d002c68a6567b Signed-off-by: Alex Waterman <alexw@nvidia.com> Signed-off-by: Deepak Nibade <dnibade@nvidia.com> Reviewed-on: http://git-master/r/1197204 (cherry picked from commit b4e68e84eedd952637b2332d8dc73a9090d6d62e) Reviewed-on: http://git-master/r/1210949 Reviewed-by: mobile promotions <svcmobile_promotions@nvidia.com> Tested-by: mobile promotions <svcmobile_promotions@nvidia.com>
* gpu: nvgpu: add aperture and size to map loggingKonsta Holtta2016-07-22
| | | | | | | | | | | | Include the buffer aperture flag (sysmem/vidmem/invalid) and the size of the buffer and of the mapping in logging strings during gmmu map path. Change-Id: Ie4c46bf9cb5db79b738571029d46ce8cbfc63f99 Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1189492 GVS: Gerrit_Virtual_Submit Reviewed-by: Alex Waterman <alexw@nvidia.com> Reviewed-by: Yu-Huan Hsu <yhsu@nvidia.com>
* gpu: nvgpu: add vidmem allocation ioctlKonsta Holtta2016-07-21
| | | | | | | | | | | | | | | | | | Add NVGPU_GPU_IOCTL_ALLOC_VIDMEM to the ctrl fd for letting userspace allocate on-board GPU memory (aka vidmem). The allocations are returned as dmabuf fds. Also, report the amount of local video memory in the gpu characteristics. Jira DNVGPU-19 Jira DNVGPU-38 Change-Id: I28e361d31bb630b96d06bb1c86d022d91c7592bc Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1181152 GVS: Gerrit_Virtual_Submit Reviewed-by: Vijayakumar Subbu <vsubbu@nvidia.com>
* gpu: nvgpu: add vidmem managerKonsta Holtta2016-07-21
| | | | | | | | | | | | | | | Use the nvgpu-internal buddy allocator for video memory allocations, instead of nvmap. This allows better integration for copyengine, BAR1 mapping to userspace, etc. Jira DNVGPU-38 Change-Id: I9fd67b76cd39721e4cd8e525ad0ed76f497e8b99 Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1181151 Reviewed-by: Automatic_Commit_Validation_User GVS: Gerrit_Virtual_Submit Reviewed-by: Vijayakumar Subbu <vsubbu@nvidia.com>
* gpu: nvgpu: Add nvgpu infra to allow kernel to create privileged CE channelsLakshmanan M2016-07-20
| | | | | | | | | | | | | Added interface to allow kernel to create privileged CE channels for page migration and clearing support between sysmem and videmem. JIRA DNVGPU-53 Change-Id: I3e18d18403809c9e64fa45d40b6c4e3844992506 Signed-off-by: Lakshmanan M <lm@nvidia.com> Reviewed-on: http://git-master/r/1173085 GVS: Gerrit_Virtual_Submit Reviewed-by: Vijayakumar Subbu <vsubbu@nvidia.com>
* gpu: nvgpu: Support multiple types of allocatorsAlex Waterman2016-07-19
| | | | | | | | | | | | | | | | | | | | | | Support multiple types of allocation backends. Currently there is only one allocator implementation available: a buddy allocator. Buddy allocators have certain limitations though. For one the allocator requires metadata to be allocated from the kernel's system memory. This causes a given buddy allocation to potentially sleep on a kmalloc() call. This patch has been created so that a new backend can be created which will avoid any dynamic system memory management routines from being called. Bug 1781897 Change-Id: I98d6c8402c049942f13fee69c6901a166f177f65 Signed-off-by: Alex Waterman <alexw@nvidia.com> Reviewed-on: http://git-master/r/1172115 GVS: Gerrit_Virtual_Submit Reviewed-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-by: Yu-Huan Hsu <yhsu@nvidia.com>
* gpu: nvgpu: handle map/unmap for vidmem gmmu pagesKonsta Holtta2016-07-14
| | | | | | | | | | | | | | | If page tables are allocated from vidmem, cpu cache flushing doesn't make sense, so skip it. Unify also map/unmap actions if the pages are not mapped. Jira DNVGPU-20 Change-Id: I36b22749aab99a7bae26c869075f8073eab0f860 Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1178830 Reviewed-by: Automatic_Commit_Validation_User GVS: Gerrit_Virtual_Submit Reviewed-by: Vijayakumar Subbu <vsubbu@nvidia.com>
* gpu: nvgpu: use vidmem by default in gmmu_alloc variantsKonsta Holtta2016-07-08
| | | | | | | | | | | | | | | | | | For devices that have vidmem available, use the vidmem allocator in gk20a_gmmu_alloc{,attr,_map,_map_attr}. For others, use sysmem. Because all of the buffers haven't been tested to work in vidmem yet, rename calls to gk20a_gmmu_alloc{,attr,_map,_map_attr} to have _sys at the end to declare explicitly that vidmem is used. Enabling vidmem for each now is a matter of removing "_sys" from the function call. Jira DNVGPU-18 Change-Id: Ibe42f67eff2c2b68c36582e978ace419dc815dc5 Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1176805 GVS: Gerrit_Virtual_Submit Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: support in-kernel vidmem mappingsKonsta Holtta2016-07-06
| | | | | | | | | | | | | | | Propagate the buffer aperture flag in gk20a_locked_gmmu_map up so that buffers represented as a mem_desc and present in vidmem can be mapped to gpu. JIRA DNVGPU-18 JIRA DNVGPU-76 Change-Id: I46cf87e27229123016727339b9349d5e2c835b3e Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1169308 GVS: Gerrit_Virtual_Submit Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: ngpu: add support for vidmem in page tablesKonsta Holtta2016-07-05
| | | | | | | | | | | | | | Modify page table updates to take an aperture flag (up until gk20a_locked_gmmu_map()), don't hard-assume sysmem and propagate it to hardware. Jira DNVGPU-76 Change-Id: Ifcb22900c96db993068edd110e09368f72b06f69 Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1169307 Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com> Tested-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: initial support for vidmem aperturesKonsta Holtta2016-07-05
| | | | | | | | | | | | | | add gk20a_aperture_mask() for memory target selection now that buffers can actually be allocated from vidmem, and use it in all cases that have a mem_desc available. Jira DNVGPU-76 Change-Id: I4353cdc6e1e79488f0875581cfaf2a5cfb8c976a Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1169306 Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com> Tested-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: Revamp semaphore supportAlex Waterman2016-06-28
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Revamp the support the nvgpu driver has for semaphores. The original problem with nvgpu's semaphore support is that it required a SW based wait for every semaphore release. This was because for every fence that gk20a_channel_semaphore_wait_fd() waited on a new semaphore was created. This semaphore would then get released by SW when the fence signaled. This meant that for every release there was necessarily a sync_fence_wait_async() call which could block. The latency of this SW wait was enough to cause massive degredation in performance. To fix this a fast path was implemented. When a fence is passed to gk20a_channel_semaphore_wait_fd() that is backed by a GPU semaphore a semaphore acquire is directly used to block the GPU. No longer is a sync_fence_wait_async() performed nor is there an extra semaphore created. To implement this fast path the semaphore memory had to be shared between channels. Previously since a new semaphore was created every time through gk20a_channel_semaphore_wait_fd() what address space a semaphore was mapped into was irrelevant. However, when using the fast path a sempahore may be released on one address space but acquired in another. Sharing the semaphore memory was done by making a fixed GPU mapping in all channels. This mapping points to the semaphore memory (the so called semaphore sea). This global fixed mapping is read-only to make sure no semaphores can be incremented (i.e released) by a malicious channel. Each channel then gets a RW mapping of it's own semaphore. This way a channel may only acquire other channel's semaphores but may both acquire and release its own semaphore. The gk20a fence code was updated to allow introspection of the GPU backed fences. This allows detection of when the fast path can be taken. If the fast path cannot be used (for example when a fence is sync-pt backed) the original slow path is still present. This gets used when the GPU needs to wait on an event from something which only understands how to use sync-pts. Bug 1732449 JIRA DNVGPU-12 Change-Id: Ic0fea74994da5819a771deac726bb0d47a33c2de Signed-off-by: Alex Waterman <alexw@nvidia.com> Reviewed-on: http://git-master/r/1133792 Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com> Tested-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: use gpfifo_mem via gk20a_mem_{rd,wr}Konsta Holtta2016-06-20
| | | | | | | | | | | | | | | | | | Use gk20a_mem_*() accessors for gpfifo memory in work submission instead of direct cpu accesses in order to support other apertures than sysmem. The gpfifo memory is still allocated from sysmem for dgpus too. Split the copying of priv_cmds and the main gpfifo to be submitted in gk20a_submit_channel_gpfifo() into separate functions. JIRA DNVGPU-21 Change-Id: If271ca8e7e34235f00d31855dbccf77c0008e10b Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1145923 Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com> Tested-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: add vidmem allocation APIKonsta Holtta2016-06-15
| | | | | | | | | | | | | | | | | | | | | | | | | | | Add in-nvgpu APIs for allocating and freeing mem_descs in video memory. Changes for gmmu tables etc. will be added in upcoming changes. Video memory is allocated via nvmap by initially registering the aperture size to it and binding it to a struct device, and then going via the usual dma alloc. This API allows also fixed-address allocations, meant for reserving special memory areas at boot. The aperture registration is skipped completely if vidmem isn't found for the particular device. gk20a_gmmu_alloc_attr() still uses sysmem, and the unmap/free paths select internally the correct path by the mem_desc's aperture. Video memory allocation is off by default, and can be turned on with CONFIG_GK20A_VIDMEM. JIRA DNVGPU-16 Change-Id: I77eae5ea90cbed6f4b5db0da86c5f70ddf2a34f9 Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1157216 GVS: Gerrit_Virtual_Submit Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: optimize mem_desc accessor loopsKonsta Holtta2016-06-13
| | | | | | | | | | | | | | Instead of going via gk20a_mem_{wr,rd}32() on each iteration, do direct memcpy/memset with sysmem, and minimize the enter/exit overhead with vidmem. JIRA DNVGPU-23 Change-Id: I5437e35f8393a746777a40636c1e9b5d93ced1f6 Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1159524 Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com> Tested-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: Remove dead priv_cmdbuf codeAlex Waterman2016-06-13
| | | | | | | | | | | | | | Remove the gp_get and gp_put pointers from the priv_cmdbuf code. These pointers appear to track the position of th the priv_cmdbuf in the gp_fifo. However, these pointers are not used for anything nor are they needed for anything in the future. This code appears to be a relic left over from the past. Change-Id: Ibed1a6d51fa0cac12c5e0429760e8e2f611fc899 Signed-off-by: Alex Waterman <alexw@nvidia.com> Reviewed-on: http://git-master/r/1161859 Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com> Tested-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: detect vidmem configuration from HWKonsta Holtta2016-06-08
| | | | | | | | | | | | | Read video memory size from hardware during initialization for devices that support it. JIRA DNVGPU-14 Change-Id: If190f2d89f7148520ee274ca674f972987c8056d Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1157215 Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com> Tested-by: Terje Bergstrom <tbergstrom@nvidia.com>
* gpu: nvgpu: cache whole bar0_window for mem accessesKonsta Holtta2016-06-07
| | | | | | | | | | | | | | Save the whole bar0 window register that encodes also the target aperture (vid/sys mem) instead of only the base address that could overlap between the two. JIRA DNVGPU-23 Change-Id: I2ccbea0e1f7c7310c1ca6b158afafe8fd974a615 Signed-off-by: Konsta Holtta <kholtta@nvidia.com> Reviewed-on: http://git-master/r/1159523 GVS: Gerrit_Virtual_Submit Reviewed-by: Terje Bergstrom <tbergstrom@nvidia.com>
generated by cgit v1.2.2 (git 2.25.0) at 2024-07-17 16:00:26 -0400