-
Notifications
You must be signed in to change notification settings - Fork 11.8k
sycl : reviewing the backend documentation #13544
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
base: master
Are you sure you want to change the base?
Changes from all commits
6761532
b01abf5
ee90037
513a5f9
230279d
501891c
38e7664
File filter
Filter by extension
Conversations
Jump to
Diff view
Diff view
There are no files selected for viewing
Original file line number | Diff line number | Diff line change | ||||
---|---|---|---|---|---|---|
|
@@ -17,25 +17,25 @@ | |||||
|
||||||
**SYCL** is a high-level parallel programming model designed to improve developers productivity writing code across various hardware accelerators such as CPUs, GPUs, and FPGAs. It is a single-source language designed for heterogeneous computing and based on standard C++17. | ||||||
|
||||||
**oneAPI** is an open ecosystem and a standard-based specification, supporting multiple architectures including but not limited to intel CPUs, GPUs and FPGAs. The key components of the oneAPI ecosystem include: | ||||||
**oneAPI** is an open ecosystem and a standard-based specification, supporting multiple architectures including but not limited to Intel CPUs, GPUs and FPGAs. The key components of the oneAPI ecosystem include: | ||||||
|
||||||
- **DPCPP** *(Data Parallel C++)*: The primary oneAPI SYCL implementation, which includes the icpx/icx Compilers. | ||||||
- **oneAPI Libraries**: A set of highly optimized libraries targeting multiple domains *(e.g. Intel oneMKL, oneMath and oneDNN)*. | ||||||
- **oneAPI LevelZero**: A high performance low level interface for fine-grained control over intel iGPUs and dGPUs. | ||||||
- **oneAPI LevelZero**: A high performance low level interface for fine-grained control over Intel iGPUs and dGPUs. | ||||||
- **Nvidia & AMD Plugins**: These are plugins extending oneAPI's DPCPP support to SYCL on Nvidia and AMD GPU targets. | ||||||
|
||||||
### Llama.cpp + SYCL | ||||||
|
||||||
The llama.cpp SYCL backend is designed to support **Intel GPU** firstly. Based on the cross-platform feature of SYCL, it also supports other vendor GPUs: Nvidia and AMD. | ||||||
The llama.cpp SYCL backend is primarily designed for **Intel GPUs**. | ||||||
SYCL cross-platform capabilities enable support for Nvidia GPUs as well, with limited support for AMD. | ||||||
|
||||||
## Recommended Release | ||||||
|
||||||
The SYCL backend would be broken by some PRs due to no online CI. | ||||||
|
||||||
The following release is verified with good quality: | ||||||
The following releases are verified and recommended: | ||||||
|
||||||
|Commit ID|Tag|Release|Verified Platform| Update date| | ||||||
|-|-|-|-|-| | ||||||
|24e86cae7219b0f3ede1d5abdf5bf3ad515cccb8|b5377 |[llama-b5377-bin-win-sycl-x64.zip](https://github.com/ggml-org/llama.cpp/releases/download/b5377/llama-b5377-bin-win-sycl-x64.zip) |ArcB580/Linux/oneAPI 2025.1<br>LNL Arc GPU/Windows 11/oneAPI 2025.1.1|2025-05-15| | ||||||
|3bcd40b3c593d14261fb2abfabad3c0fb5b9e318|b4040 |[llama-b4040-bin-win-sycl-x64.zip](https://github.com/ggml-org/llama.cpp/releases/download/b4040/llama-b4040-bin-win-sycl-x64.zip) |Arc770/Linux/oneAPI 2024.1<br>MTL Arc GPU/Windows 11/oneAPI 2024.1| 2024-11-19| | ||||||
|fb76ec31a9914b7761c1727303ab30380fd4f05c|b3038 |[llama-b3038-bin-win-sycl-x64.zip](https://github.com/ggml-org/llama.cpp/releases/download/b3038/llama-b3038-bin-win-sycl-x64.zip) |Arc770/Linux/oneAPI 2024.1<br>MTL Arc GPU/Windows 11/oneAPI 2024.1|| | ||||||
|
||||||
|
@@ -106,15 +106,14 @@ SYCL backend supports Intel GPU Family: | |||||
|-------------------------------|---------|---------------------------------------| | ||||||
| Intel Data Center Max Series | Support | Max 1550, 1100 | | ||||||
| Intel Data Center Flex Series | Support | Flex 170 | | ||||||
| Intel Arc Series | Support | Arc 770, 730M, Arc A750 | | ||||||
| Intel built-in Arc GPU | Support | built-in Arc GPU in Meteor Lake, Arrow Lake | | ||||||
| Intel iGPU | Support | iGPU in 13700k,iGPU in 13400, i5-1250P, i7-1260P, i7-1165G7 | | ||||||
| Intel Arc Series | Support | Arc 770, 730M, Arc A750, B580 | | ||||||
| Intel built-in Arc GPU | Support | built-in Arc GPU in Meteor Lake, Arrow Lake, Lunar Lake | | ||||||
| Intel iGPU | Support | iGPU in 13700k, 13400, i5-1250P, i7-1260P, i7-1165G7 | | ||||||
|
||||||
*Notes:* | ||||||
|
||||||
- **Memory** | ||||||
- The device memory is a limitation when running a large model. The loaded model size, *`llm_load_tensors: buffer_size`*, is displayed in the log when running `./bin/llama-cli`. | ||||||
|
||||||
- Please make sure the GPU shared memory from the host is large enough to account for the model's size. For e.g. the *llama-2-7b.Q4_0* requires at least 8.0GB for integrated GPU and 4.0GB for discrete GPU. | ||||||
|
||||||
- **Execution Unit (EU)** | ||||||
|
@@ -138,19 +137,22 @@ Note: AMD GPU support is highly experimental and is incompatible with F16. | |||||
Additionally, it only supports GPUs with a sub_group_size (warp size) of 32. | ||||||
|
||||||
## Docker | ||||||
The docker build option is currently limited to *intel GPU* targets. | ||||||
|
||||||
The docker build option is currently limited to *Intel GPU* targets. | ||||||
|
||||||
### Build image | ||||||
|
||||||
```sh | ||||||
# Using FP16 | ||||||
docker build -t llama-cpp-sycl --build-arg="GGML_SYCL_F16=ON" --target light -f .devops/intel.Dockerfile . | ||||||
``` | ||||||
|
||||||
*Notes*: | ||||||
|
||||||
To build in default FP32 *(Slower than FP16 alternative)*, you can remove the `--build-arg="GGML_SYCL_F16=ON"` argument from the previous command. | ||||||
To build in default FP32 *(Slower than FP16 alternative)*, set `--build-arg="GGML_SYCL_F16=OFF"` in the previous command. | ||||||
|
||||||
You can also use the `.devops/llama-server-intel.Dockerfile`, which builds the *"server"* alternative. | ||||||
Check the [documentation for Docker](../docker.md) to see the available images. | ||||||
|
||||||
### Run container | ||||||
|
||||||
|
@@ -250,7 +252,7 @@ sycl-ls | |||||
|
||||||
- **Intel GPU** | ||||||
|
||||||
When targeting an intel GPU, the user should expect one or more level-zero devices among the available SYCL devices. Please make sure that at least one GPU is present, for instance [`level_zero:gpu`] in the sample output below: | ||||||
When targeting an intel GPU, the user should expect one or more level-zero devices among the available SYCL devices. Please make sure that at least one GPU is present, for instance `[level_zero:gpu]` in the sample output below: | ||||||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. This seems to convey that level zero is absolutely required, Could we maybe rephrase it to something along the lines of: |
||||||
|
||||||
``` | ||||||
[opencl:acc][opencl:0] Intel(R) FPGA Emulation Platform for OpenCL(TM), Intel(R) FPGA Emulation Device OpenCL 1.2 [2023.16.10.0.17_160000] | ||||||
|
@@ -282,7 +284,7 @@ For AMD GPUs we should expect at least one SYCL-HIP device [`hip:gpu`]: | |||||
|
||||||
#### Intel GPU | ||||||
|
||||||
``` | ||||||
```sh | ||||||
./examples/sycl/build.sh | ||||||
``` | ||||||
|
||||||
|
@@ -351,7 +353,7 @@ cmake --build build --config Release -j -v | |||||
|
||||||
#### Retrieve and prepare model | ||||||
|
||||||
You can refer to the general [*Prepare and Quantize*](README.md#prepare-and-quantize) guide for model prepration, or simply download [llama-2-7b.Q4_0.gguf](https://huggingface.co/TheBloke/Llama-2-7B-GGUF/blob/main/llama-2-7b.Q4_0.gguf) model as example. | ||||||
You can refer to the general [*Prepare and Quantize*](README.md#prepare-and-quantize) guide for model preparation, or download an already quantized model like [llama-2-7b.Q4_0.gguf](https://huggingface.co/TheBloke/Llama-2-7B-GGUF/blob/main/llama-2-7b.Q4_0.gguf) or [Meta-Llama-3-8B-Instruct-Q4_0.gguf](https://huggingface.co/aptha/Meta-Llama-3-8B-Instruct-Q4_0-GGUF/resolve/main/Meta-Llama-3-8B-Instruct-Q4_0.gguf). | ||||||
|
||||||
##### Check device | ||||||
|
||||||
|
@@ -398,11 +400,15 @@ Choose one of following methods to run. | |||||
|
||||||
```sh | ||||||
./examples/sycl/run-llama2.sh 0 | ||||||
# OR | ||||||
./examples/sycl/run-llama3.sh 0 | ||||||
``` | ||||||
- Use multiple devices: | ||||||
|
||||||
```sh | ||||||
./examples/sycl/run-llama2.sh | ||||||
# OR | ||||||
./examples/sycl/run-llama3.sh | ||||||
``` | ||||||
|
||||||
2. Command line | ||||||
|
@@ -425,13 +431,13 @@ Examples: | |||||
- Use device 0: | ||||||
|
||||||
```sh | ||||||
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -no-cnv -m models/llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 33 -sm none -mg 0 | ||||||
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -no-cnv -m models/llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 99 -sm none -mg 0 | ||||||
``` | ||||||
|
||||||
- Use multiple devices: | ||||||
|
||||||
```sh | ||||||
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -no-cnv -m models/llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 33 -sm layer | ||||||
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -no-cnv -m models/llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 99 -sm layer | ||||||
``` | ||||||
|
||||||
*Notes:* | ||||||
|
@@ -452,7 +458,7 @@ use 1 SYCL GPUs: [0] with Max compute units:512 | |||||
|
||||||
1. Install GPU driver | ||||||
|
||||||
Intel GPU drivers instructions guide and download page can be found here: [Get intel GPU Drivers](https://www.intel.com/content/www/us/en/products/docs/discrete-gpus/arc/software/drivers.html). | ||||||
Intel GPU drivers instructions guide and download page can be found here: [Get Intel GPU Drivers](https://www.intel.com/content/www/us/en/products/docs/discrete-gpus/arc/software/drivers.html). | ||||||
|
||||||
2. Install Visual Studio | ||||||
|
||||||
|
@@ -629,7 +635,7 @@ Once it is completed, final results will be in **build/Release/bin** | |||||
|
||||||
#### Retrieve and prepare model | ||||||
|
||||||
You can refer to the general [*Prepare and Quantize*](README.md#prepare-and-quantize) guide for model prepration, or simply download [llama-2-7b.Q4_0.gguf](https://huggingface.co/TheBloke/Llama-2-7B-GGUF/blob/main/llama-2-7b.Q4_0.gguf) model as example. | ||||||
You can refer to the general [*Prepare and Quantize*](README.md#prepare-and-quantize) guide for model preparation, or download an already quantized model like [llama-2-7b.Q4_0.gguf](https://huggingface.co/TheBloke/Llama-2-7B-GGUF/blob/main/llama-2-7b.Q4_0.gguf) or [Meta-Llama-3-8B-Instruct-Q4_0.gguf](https://huggingface.co/aptha/Meta-Llama-3-8B-Instruct-Q4_0-GGUF/resolve/main/Meta-Llama-3-8B-Instruct-Q4_0.gguf). | ||||||
|
||||||
##### Check device | ||||||
|
||||||
|
@@ -648,7 +654,7 @@ Similar to the native `sycl-ls`, available SYCL devices can be queried as follow | |||||
build\bin\llama-ls-sycl-device.exe | ||||||
``` | ||||||
|
||||||
This command will only display the selected backend that is supported by SYCL. The default backend is level_zero. For example, in a system with 2 *intel GPU* it would look like the following: | ||||||
This command will only display the selected backend that is supported by SYCL. The default backend is level_zero. For example, in a system with 2 *Intel GPU* it would look like the following: | ||||||
``` | ||||||
found 2 SYCL devices: | ||||||
| | | |Compute |Max compute|Max work|Max sub| | | ||||||
|
@@ -658,13 +664,14 @@ found 2 SYCL devices: | |||||
| 1|[level_zero:gpu:1]| Intel(R) UHD Graphics 770| 1.3| 32| 512| 32| 53651849216| | ||||||
``` | ||||||
|
||||||
#### Choose level-zero devices | ||||||
|
||||||
|Chosen Device ID|Setting| | ||||||
|-|-| | ||||||
|0|`set ONEAPI_DEVICE_SELECTOR="level_zero:1"` or no action| | ||||||
|0|Default option. You may also want to `set ONEAPI_DEVICE_SELECTOR="level_zero:0"`| | ||||||
|1|`set ONEAPI_DEVICE_SELECTOR="level_zero:1"`| | ||||||
|0 & 1|`set ONEAPI_DEVICE_SELECTOR="level_zero:0;level_zero:1"`| | ||||||
|0 & 1|`set ONEAPI_DEVICE_SELECTOR="level_zero:0;level_zero:1"` or `set ONEAPI_DEVICE_SELECTOR="level_zero:*"`| | ||||||
|
||||||
#### Execute | ||||||
|
||||||
|
@@ -673,7 +680,13 @@ Choose one of following methods to run. | |||||
1. Script | ||||||
|
||||||
``` | ||||||
examples\sycl\win-run-llama2.bat | ||||||
examples\sycl\win-run-llama-2.bat | ||||||
``` | ||||||
|
||||||
or | ||||||
|
||||||
``` | ||||||
examples\sycl\win-run-llama-3.bat | ||||||
``` | ||||||
|
||||||
2. Command line | ||||||
|
@@ -697,13 +710,13 @@ Examples: | |||||
- Use device 0: | ||||||
|
||||||
``` | ||||||
build\bin\llama-cli.exe -no-cnv -m models\llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:\nStep 1:" -n 400 -e -ngl 33 -s 0 -sm none -mg 0 | ||||||
build\bin\llama-cli.exe -no-cnv -m models\llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:\nStep 1:" -n 400 -e -ngl 99 -sm none -mg 0 | ||||||
``` | ||||||
|
||||||
- Use multiple devices: | ||||||
|
||||||
``` | ||||||
build\bin\llama-cli.exe -no-cnv -m models\llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:\nStep 1:" -n 400 -e -ngl 33 -s 0 -sm layer | ||||||
build\bin\llama-cli.exe -no-cnv -m models\llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:\nStep 1:" -n 400 -e -ngl 99 -sm layer | ||||||
``` | ||||||
|
||||||
|
||||||
|
@@ -714,7 +727,9 @@ Note: | |||||
```sh | ||||||
detect 1 SYCL GPUs: [0] with top Max compute units:512 | ||||||
``` | ||||||
|
||||||
Or | ||||||
|
||||||
```sh | ||||||
use 1 SYCL GPUs: [0] with Max compute units:512 | ||||||
``` | ||||||
|
@@ -726,14 +741,16 @@ use 1 SYCL GPUs: [0] with Max compute units:512 | |||||
|
||||||
| Name | Value | Function | | ||||||
|--------------------|---------------------------------------|---------------------------------------------| | ||||||
| GGML_SYCL | ON (mandatory) | Enable build with SYCL code path.<br>FP32 path - recommended for better perforemance than FP16 on quantized model| | ||||||
| GGML_SYCL | ON (mandatory) | Enable build with SYCL code path. | | ||||||
| GGML_SYCL_TARGET | INTEL *(default)* \| NVIDIA \| AMD | Set the SYCL target device type. | | ||||||
| GGML_SYCL_DEVICE_ARCH | Optional (except for AMD) | Set the SYCL device architecture, optional except for AMD. Setting the device architecture can improve the performance. See the table [--offload-arch](https://github.com/intel/llvm/blob/sycl/sycl/doc/design/OffloadDesign.md#--offload-arch) for a list of valid architectures. | | ||||||
| GGML_SYCL_F16 | OFF *(default)* \|ON *(optional)* | Enable FP16 build with SYCL code path. | | ||||||
| GGML_SYCL_F16 | OFF *(default)* \|ON *(optional)* | Enable FP16 build with SYCL code path. (1.) | | ||||||
| GGML_SYCL_GRAPH | ON *(default)* \|OFF *(Optional)* | Enable build with [SYCL Graph extension](https://github.com/intel/llvm/blob/sycl/sycl/doc/extensions/experimental/sycl_ext_oneapi_graph.asciidoc). | | ||||||
| CMAKE_C_COMPILER | `icx` *(Linux)*, `icx/cl` *(Windows)* | Set `icx` compiler for SYCL code path. | | ||||||
| CMAKE_CXX_COMPILER | `icpx` *(Linux)*, `icx` *(Windows)* | Set `icpx/icx` compiler for SYCL code path. | | ||||||
|
||||||
1. FP16 is recommended for better prompt processing performance on quantized models. Performance is equivalent in text generation but set `GGML_SYCL_F16=OFF` if you are experiencing issues with FP16 builds. | ||||||
|
||||||
#### Runtime | ||||||
|
||||||
| Name | Value | Function | | ||||||
|
@@ -750,7 +767,7 @@ use 1 SYCL GPUs: [0] with Max compute units:512 | |||||
|
||||||
## Q&A | ||||||
|
||||||
- Error: `error while loading shared libraries: libsycl.so.7: cannot open shared object file: No such file or directory`. | ||||||
- Error: `error while loading shared libraries: libsycl.so.8: cannot open shared object file: No such file or directory`. | ||||||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more.
Suggested change
so that we needn't update with every release, just mentioning libsycl.so is sufficient |
||||||
|
||||||
- Potential cause: Unavailable oneAPI installation or not set ENV variables. | ||||||
- Solution: Install *oneAPI base toolkit* and enable its ENV through: `source /opt/intel/oneapi/setvars.sh`. | ||||||
|
@@ -779,18 +796,18 @@ use 1 SYCL GPUs: [0] with Max compute units:512 | |||||
|
||||||
It's same for other projects including llama.cpp SYCL backend. | ||||||
|
||||||
- Meet issue: `Native API failed. Native API returns: -6 (PI_ERROR_OUT_OF_HOST_MEMORY) -6 (PI_ERROR_OUT_OF_HOST_MEMORY) -999 (UNKNOWN PI error)` or `failed to allocate SYCL0 buffer` | ||||||
- `Native API failed. Native API returns: 39 (UR_RESULT_ERROR_OUT_OF_DEVICE_MEMORY)`, `ggml_backend_sycl_buffer_type_alloc_buffer: can't allocate 3503030272 Bytes of memory on device`, or `failed to allocate SYCL0 buffer` | ||||||
NeoZhangJianyu marked this conversation as resolved.
Show resolved
Hide resolved
|
||||||
|
||||||
Device Memory is not enough. | ||||||
You are running out of Device Memory. | ||||||
|
||||||
|Reason|Solution| | ||||||
|-|-| | ||||||
|Default Context is too big. It leads to more memory usage.|Set `-c 8192` or smaller value.| | ||||||
|Model is big and require more memory than device's.|Choose smaller quantized model, like Q5 -> Q4;<br>Use more than one devices to load model.| | ||||||
| The default context is too big. It leads to excessive memory usage.|Set `-c 8192` or a smaller value.| | ||||||
| The model is too big and requires more memory than what is available.|Choose a smaller model or change to a smaller quantization, like Q5 -> Q4;<br>Alternatively, use more than one device to load model.| | ||||||
|
||||||
### **GitHub contribution**: | ||||||
Please add the **[SYCL]** prefix/tag in issues/PRs titles to help the SYCL-team check/address them without delay. | ||||||
Please add the `SYCL :` prefix/tag in issues/PRs titles to help the SYCL contributors to check/address them without delay. | ||||||
|
||||||
## TODO | ||||||
|
||||||
- NA | ||||||
- Review ZES_ENABLE_SYSMAN: https://github.com/intel/compute-runtime/blob/master/programmers-guide/SYSMAN.md#support-and-limitations |
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,26 @@ | ||
#!/bin/bash | ||
|
||
# MIT license | ||
# Copyright (C) 2025 Intel Corporation | ||
# SPDX-License-Identifier: MIT | ||
|
||
export ONEAPI_DEVICE_SELECTOR="level_zero:0" | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. any reason we are selecting this particularly ? Is this required ? There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. The code will choose all Intel GPUs in the PC. |
||
source /opt/intel/oneapi/setvars.sh | ||
|
||
#export GGML_SYCL_DEBUG=1 | ||
|
||
#ZES_ENABLE_SYSMAN=1, Support to get free memory of GPU by sycl::aspect::ext_intel_free_memory. Recommended to use when --split-mode = layer. | ||
|
||
INPUT_PROMPT="Building a website can be done in 10 simple steps:\nStep 1:" | ||
MODEL_FILE=models/Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf | ||
NGL=99 # Layers offloaded to the GPU. If the device runs out of memory, reduce this value according to the model you are using. | ||
CONTEXT=4096 | ||
|
||
if [ $# -gt 0 ]; then | ||
GGML_SYCL_DEVICE=$1 | ||
echo "Using $GGML_SYCL_DEVICE as the main GPU" | ||
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -m ${MODEL_FILE} -p "${INPUT_PROMPT}" -n 400 -e -ngl ${NGL} -c ${CONTEXT} -mg $GGML_SYCL_DEVICE -sm none | ||
else | ||
#use multiple GPUs with same max compute units | ||
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -m ${MODEL_FILE} -p "${INPUT_PROMPT}" -n 400 -e -ngl ${NGL} -c ${CONTEXT} | ||
fi |
Original file line number | Diff line number | Diff line change | ||||
---|---|---|---|---|---|---|
@@ -0,0 +1,9 @@ | ||||||
:: MIT license | ||||||
:: Copyright (C) 2024 Intel Corporation | ||||||
:: SPDX-License-Identifier: MIT | ||||||
|
||||||
set INPUT2="Building a website can be done in 10 simple steps:\nStep 1:" | ||||||
@call "C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64 --force | ||||||
|
||||||
|
||||||
.\build\bin\llama-cli.exe -m models\Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf -p %INPUT2% -n 400 -e -ngl 33 | ||||||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more.
Suggested change
|
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
These two lines convey more or less the same thing ?
Maybe let's remove the below one ? so that we needn't keep appending it time and again.
Also it's better to just mention the architecture than a very specific CPU model, as it will cover all the cases for that series.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
I would also remove the word "Arc" from above, as technically B580 and Lunar lake are not a part of the Arc series.
Lets rename that column from "Intel Arc Series" to say "Intel Discrete GPUs" ?
Similarly for the one below, "Intel Built-in Arc GPU" to just "Intel iGPUs"
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
List the detailed models will help use to check easily.
First line are the new iGPU based on Arc GPU. They are powerful than next line.
Next line is the old arch iGPU. Some user still hope run LLM on them. SYCL backend support it will make the ecosystem better on Intel GPU.
"Arc" is the common commercial name of Intel GPU.
B580's full name should be: Intel Arc B580.
So, here is correct.