Open Maetveis opened 1 year ago
Hi @Maetveis ,
(Not an AMD employee here, but going to try to help.)
I guess you probably moved on to something else, but if anything, I would recommend to open a bug ticket in LLVM instead, as maybe it is something the compiler can be taught to improve potentially.
Your code seems wrong due to all threads writing into c[0]
, but I assume that it was a typo when writing your message, or a big part of the code is missing due to using c-reduce.
From basic experience, reaching max performance on RDNA can be quite challenging compared to GCN.
While hard to tell and profiling being quite hard on RDNA, I suspect that you might be hitting one these issues:
1) bad write coalescing when writing h
, that somehow gets better when putting the load. I have observed that putting synchronizations (with syncthreads()
) can sometimes improve performance by improving write coalescing
2) if you are really have all your threads writing into c[0]
, depending on your blocksize, the load might help with avoiding all threads are hitting the LDS at the same time and the LDS serializes less all the writes
Anyway, that's pure guessing. Best, Epliz
Thanks, @Epliz for the suggestions, I replied to them below
I guess you probably moved on to something else
I am still interested in this as solving it would unblock upstreaming an optimization in vkFFT for AMDGPU, as well as potentially improve many kernels on RDNA2 if the root cause can be fixed.
I would recommend to open a bug ticket in LLVM instead, as maybe it is something the compiler can be taught to improve potentially.
For this specific issue I don't think the compiler is involved because it can be reproduced by changing the generated assembly (removing the load instruction for blockDim
).
--- test.s 2023-01-31 08:43:20.798273297 +0000
+++ test.noasm.s 2023-01-31 08:44:16.353553582 +0000
@@ -7,7 +7,7 @@
VkFFT_main: ; @VkFFT_main
; %bb.0:
s_load_dwordx4 s[0:3], s[6:7], 0x0
- s_load_dword s4, s[4:5], 0x4
+ ;s_load_dword s4, s[4:5], 0x4
v_add_nc_u32_e32 v3, v1, v0
v_mul_u32_u24_e32 v1, 7, v1
s_mulk_i32 s9, 0x18f0
Your code seems wrong due to all threads writing into c[0], but I assume that it was a typo when writing your message, or a big part of the code is missing due to using c-reduce.
Yes its the effect of the reduction, using different locations for each thread still reproduces the problem, using the same location (while technically UB due to the race condition) results in a simpler assembly.
My guess was something to do with the command processor (CP)1 not caching the dispatch packet, but accessing it from the kernel (to read blockDim
from it) leaves it in cache for subsequent blocks. This is supported by the fact that the following change (loading the kernarg pointer by hand; which is also done by the CP) also result in the faster performing kernel.
--- test.s 2023-01-31 09:35:20.406608882 +0000
+++ test.noasm.s 2023-01-31 09:37:13.877167577 +0000
@@ -6,8 +6,9 @@
.type VkFFT_main,@function
VkFFT_main: ; @VkFFT_main
; %bb.0:
+ s_load_dwordx2 s[6:7], s[4:5], 0x28
s_load_dwordx4 s[0:3], s[6:7], 0x0
- s_load_dword s4, s[4:5], 0x4
+ ;s_load_dword s4, s[4:5], 0x4
v_add_nc_u32_e32 v3, v1, v0
v_mul_u32_u24_e32 v1, 7, v1
s_mulk_i32 s9, 0x18f0
The following kernel:
becomes ~10% slower when the inline assembly for loading
blockDim.x
is removed. This seems to happen only on RDNA2 (tested with V620 and RX6650XT) on Linux.Observations
c
the slowdown becomes less without loadingblockDim
blockDim
is almost identical, differing only by the load of the block size from the dispatch packet and the metadata that flags that the dispatch packet is in use.Motivation
The kernel above was produced using c-reduce on a kernel extracted from vkFFT. A possible optimization for VkFFT's HIP backend aimed to replace
blockDim
with it's values ahead of time as they are known when compilation happens. This results in big improvements especially for small problem sizes, except select cases in RDNA2, where it leads to a slowdown as much as ~30%. This issue is the result of investigating the cause of this.Environment
hipconfig
```console ❯ hipconfig HIP version : 5.3.22061-e8e78f1a == hipconfig HIP_PATH : /opt/rocm-5.3.0 ROCM_PATH : /opt/rocm-5.3.0 HIP_COMPILER : clang HIP_PLATFORM : amd HIP_RUNTIME : rocclr CPP_CONFIG : -D__HIP_PLATFORM_HCC__= -D__HIP_PLATFORM_AMD__= -I/opt/rocm-5.3.0/include -I/opt/rocm-5.3.0/llvm/bin/../lib/clang/15.0.0 -I/opt/rocm-5.3.0/hsa/include == hip-clang HSA_PATH : /opt/rocm-5.3.0/hsa HIP_CLANG_PATH : /opt/rocm-5.3.0/llvm/bin AMD clang version 15.0.0 (https://github.com/RadeonOpenCompute/llvm-project roc-5.3.0 22362 3cf23f77f8208174a2ee7c616f4be23674d7b081) Target: x86_64-unknown-linux-gnu Thread model: posix InstalledDir: /opt/rocm-5.3.0/llvm/bin AMD LLVM version 15.0.0git Optimized build. Default target: x86_64-unknown-linux-gnu Host CPU: znver3 Registered Targets: amdgcn - AMD GCN GPUs r600 - AMD GPUs HD2XXX-HD6XXX x86 - 32-bit X86: Pentium-Pro and above x86-64 - 64-bit X86: EM64T and AMD64 hip-clang-cxxflags : -std=c++11 -isystem "/opt/rocm-5.3.0/llvm/lib/clang/15.0.0/include/.." -isystem /opt/rocm-5.3.0/hsa/include -isystem "/opt/rocm-5.3.0/include" -O3 hip-clang-ldflags : -L"/opt/rocm-5.3.0/lib" -O3 -lgcc_s -lgcc -lpthread -lm -lrt === Environment Variables PATH=/home/gergely/.local/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin == Linux Kernel Hostname : nostromo Linux nostromo 5.4.0-131-generic #147-Ubuntu SMP Fri Oct 14 17:07:22 UTC 2022 x86_64 x86_64 x86_64 GNU/Linux No LSB modules are available. Distributor ID: Ubuntu Description: Ubuntu 20.04.5 LTS Release: 20.04 Codename: focal ```clang version
```console ❯ /opt/rocm/llvm/bin/clang++ --version AMD clang version 15.0.0 (https://github.com/RadeonOpenCompute/llvm-project roc-5.3.0 22362 3cf23f77f8208174a2ee7c616f4be23674d7b081) Target: x86_64-unknown-linux-gnu Thread model: posix InstalledDir: /opt/rocm/llvm/bin ```rocminfo
```console ❯ rocminfo ROCk module is loaded ===================== HSA System Attributes ===================== Runtime Version: 1.1 System Timestamp Freq.: 1000.000000MHz Sig. Max Wait Duration: 18446744073709551615 (0xFFFFFFFFFFFFFFFF) (timestamp count) Machine Model: LARGE System Endianness: LITTLE ========== HSA Agents ========== ******* Agent 1 ******* Name: AMD EPYC 7713P 64-Core Processor Uuid: CPU-XX Marketing Name: AMD EPYC 7713P 64-Core Processor Vendor Name: CPU Feature: None specified Profile: FULL_PROFILE Float Round Mode: NEAR Max Queue Number: 0(0x0) Queue Min Size: 0(0x0) Queue Max Size: 0(0x0) Queue Type: MULTI Node: 0 Device Type: CPU Cache Info: L1: 32768(0x8000) KB Chip ID: 0(0x0) ASIC Revision: 0(0x0) Cacheline Size: 64(0x40) Max Clock Freq. (MHz): 2000 BDFID: 0 Internal Node ID: 0 Compute Unit: 128 SIMDs per CU: 0 Shader Engines: 0 Shader Arrs. per Eng.: 0 WatchPts on Addr. Ranges:1 Features: None Pool Info: Pool 1 Segment: GLOBAL; FLAGS: FINE GRAINED Size: 528082872(0x1f79e7b8) KB Allocatable: TRUE Alloc Granule: 4KB Alloc Alignment: 4KB Accessible by all: TRUE Pool 2 Segment: GLOBAL; FLAGS: KERNARG, FINE GRAINED Size: 528082872(0x1f79e7b8) KB Allocatable: TRUE Alloc Granule: 4KB Alloc Alignment: 4KB Accessible by all: TRUE Pool 3 Segment: GLOBAL; FLAGS: COARSE GRAINED Size: 528082872(0x1f79e7b8) KB Allocatable: TRUE Alloc Granule: 4KB Alloc Alignment: 4KB Accessible by all: TRUE ISA Info: ******* Agent 2 ******* Name: gfx1030 Uuid: GPU-abcb45dca7663b11 Marketing Name: AMD Radeon PRO V620 Vendor Name: AMD Feature: KERNEL_DISPATCH Profile: BASE_PROFILE Float Round Mode: NEAR Max Queue Number: 128(0x80) Queue Min Size: 64(0x40) Queue Max Size: 131072(0x20000) Queue Type: MULTI Node: 1 Device Type: GPU Cache Info: L1: 16(0x10) KB L2: 4096(0x1000) KB L3: 131072(0x20000) KB Chip ID: 29601(0x73a1) ASIC Revision: 1(0x1) Cacheline Size: 64(0x40) Max Clock Freq. (MHz): 2570 BDFID: 33536 Internal Node ID: 1 Compute Unit: 72 SIMDs per CU: 2 Shader Engines: 8 Shader Arrs. per Eng.: 2 WatchPts on Addr. Ranges:4 Features: KERNEL_DISPATCH Fast F16 Operation: TRUE Wavefront Size: 32(0x20) Workgroup Max Size: 1024(0x400) Workgroup Max Size per Dimension: x 1024(0x400) y 1024(0x400) z 1024(0x400) Max Waves Per CU: 32(0x20) Max Work-item Per CU: 1024(0x400) Grid Max Size: 4294967295(0xffffffff) Grid Max Size per Dimension: x 4294967295(0xffffffff) y 4294967295(0xffffffff) z 4294967295(0xffffffff) Max fbarriers/Workgrp: 32 Pool Info: Pool 1 Segment: GLOBAL; FLAGS: COARSE GRAINED Size: 31440896(0x1dfc000) KB Allocatable: TRUE Alloc Granule: 4KB Alloc Alignment: 4KB Accessible by all: FALSE Pool 2 Segment: GROUP Size: 64(0x40) KB Allocatable: FALSE Alloc Granule: 0KB Alloc Alignment: 0KB Accessible by all: FALSE ISA Info: ISA 1 Name: amdgcn-amd-amdhsa--gfx1030 Machine Models: HSA_MACHINE_MODEL_LARGE Profiles: HSA_PROFILE_BASE Default Rounding Mode: NEAR Default Rounding Mode: NEAR Fast f16: TRUE Workgroup Max Size: 1024(0x400) Workgroup Max Size per Dimension: x 1024(0x400) y 1024(0x400) z 1024(0x400) Grid Max Size: 4294967295(0xffffffff) Grid Max Size per Dimension: x 4294967295(0xffffffff) y 4294967295(0xffffffff) z 4294967295(0xffffffff) FBarrier Max Size: 32 ******* Agent 3 ******* Name: gfx1030 Uuid: GPU-2293a876b6331dff Marketing Name: AMD Radeon PRO V620 Vendor Name: AMD Feature: KERNEL_DISPATCH Profile: BASE_PROFILE Float Round Mode: NEAR Max Queue Number: 128(0x80) Queue Min Size: 64(0x40) Queue Max Size: 131072(0x20000) Queue Type: MULTI Node: 2 Device Type: GPU Cache Info: L1: 16(0x10) KB L2: 4096(0x1000) KB L3: 131072(0x20000) KB Chip ID: 29601(0x73a1) ASIC Revision: 1(0x1) Cacheline Size: 64(0x40) Max Clock Freq. (MHz): 2570 BDFID: 34304 Internal Node ID: 2 Compute Unit: 72 SIMDs per CU: 2 Shader Engines: 8 Shader Arrs. per Eng.: 2 WatchPts on Addr. Ranges:4 Features: KERNEL_DISPATCH Fast F16 Operation: TRUE Wavefront Size: 32(0x20) Workgroup Max Size: 1024(0x400) Workgroup Max Size per Dimension: x 1024(0x400) y 1024(0x400) z 1024(0x400) Max Waves Per CU: 32(0x20) Max Work-item Per CU: 1024(0x400) Grid Max Size: 4294967295(0xffffffff) Grid Max Size per Dimension: x 4294967295(0xffffffff) y 4294967295(0xffffffff) z 4294967295(0xffffffff) Max fbarriers/Workgrp: 32 Pool Info: Pool 1 Segment: GLOBAL; FLAGS: COARSE GRAINED Size: 31440896(0x1dfc000) KB Allocatable: TRUE Alloc Granule: 4KB Alloc Alignment: 4KB Accessible by all: FALSE Pool 2 Segment: GROUP Size: 64(0x40) KB Allocatable: FALSE Alloc Granule: 0KB Alloc Alignment: 0KB Accessible by all: FALSE ISA Info: ISA 1 Name: amdgcn-amd-amdhsa--gfx1030 Machine Models: HSA_MACHINE_MODEL_LARGE Profiles: HSA_PROFILE_BASE Default Rounding Mode: NEAR Default Rounding Mode: NEAR Fast f16: TRUE Workgroup Max Size: 1024(0x400) Workgroup Max Size per Dimension: x 1024(0x400) y 1024(0x400) z 1024(0x400) Grid Max Size: 4294967295(0xffffffff) Grid Max Size per Dimension: x 4294967295(0xffffffff) y 4294967295(0xffffffff) z 4294967295(0xffffffff) FBarrier Max Size: 32 *** Done *** ```Attachments
Archive file
blockdim-faster-linux-rdna2.tar.gz
containing the original VkFFT kernel, the host code used to do the speed tests (based on the launch params done by VkFFT), annotated assembly from the kernel and the script used for the test case reduction. The script is useful to verify the slowdown. It compiles and runs the kernel reduced kernel source (test.hip
) with and without loadingblockDim
up to 3 times and shows the difference in time taken.