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| -rw-r--r-- | LICENSE-APACHE | 176 | ||||
| -rw-r--r-- | LICENSE-MIT | 23 | ||||
| -rw-r--r-- | README.md | 16 |
3 files changed, 209 insertions, 6 deletions
diff --git a/LICENSE-APACHE b/LICENSE-APACHE new file mode 100644 index 0000000..1b5ec8b --- /dev/null +++ b/LICENSE-APACHE @@ -0,0 +1,176 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + +TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + +1. Definitions. + + "License" shall mean the terms and conditions for use, reproduction, + and distribution as defined by Sections 1 through 9 of this document. + + "Licensor" shall mean the copyright owner or entity authorized by + the copyright owner that is granting the License. + + "Legal Entity" shall mean the union of the acting entity and all + other entities that control, are controlled by, or are under common + control with that entity. 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In no event and under no legal theory, + whether in tort (including negligence), contract, or otherwise, + unless required by applicable law (such as deliberate and grossly + negligent acts) or agreed to in writing, shall any Contributor be + liable to You for damages, including any direct, indirect, special, + incidental, or consequential damages of any character arising as a + result of this License or out of the use or inability to use the + Work (including but not limited to damages for loss of goodwill, + work stoppage, computer failure or malfunction, or any and all + other commercial damages or losses), even if such Contributor + has been advised of the possibility of such damages. + +9. Accepting Warranty or Additional Liability. While redistributing + the Work or Derivative Works thereof, You may choose to offer, + and charge a fee for, acceptance of support, warranty, indemnity, + or other liability obligations and/or rights consistent with this + License. However, in accepting such obligations, You may act only + on Your own behalf and on Your sole responsibility, not on behalf + of any other Contributor, and only if You agree to indemnify, + defend, and hold each Contributor harmless for any liability + incurred by, or claims asserted against, such Contributor by reason + of your accepting any such warranty or additional liability. + +END OF TERMS AND CONDITIONS diff --git a/LICENSE-MIT b/LICENSE-MIT new file mode 100644 index 0000000..31aa793 --- /dev/null +++ b/LICENSE-MIT @@ -0,0 +1,23 @@ +Permission is hereby granted, free of charge, to any +person obtaining a copy of this software and associated +documentation files (the "Software"), to deal in the +Software without restriction, including without +limitation the rights to use, copy, modify, merge, +publish, distribute, sublicense, and/or sell copies of +the Software, and to permit persons to whom the Software +is furnished to do so, subject to the following +conditions: + +The above copyright notice and this permission notice +shall be included in all copies or substantial portions +of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF +ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED +TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A +PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT +SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY +CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION +OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR +IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER +DEALINGS IN THE SOFTWARE. @@ -26,7 +26,7 @@ Overall in this suite of benchmarks faster by approximately 4% on ZLUDA. * Why is OpenCL faster in Canny and Horizon Detection?\ Authors of CUDA benchmarks used CUDA functions `atomicInc` and `atomicDec` which have direct hardware support on NVIDIA cards, but no hardware support on Intel cards. They have to be emulated in software, which limits performance * Why are some benchmarks failing?\ - ZLUDA itself supports all the operations used in the failing benchmarks. From the limited debugging that has been done yet, the problem is most likely somewhere else. Intel GPU compiler stack is very capable when it comes to compiling OpenCL, C for Metal and DPC++. It's not yet very good at compiling ZLUDA. ZLUDA emits code patterns never seen before by the Intel GPU compiler stack and hits some rarely used (or not used before) code paths in the compiler.\ + ZLUDA itself supports all the operations used in the failing benchmarks. From the limited debugging that has been done so far, the problem is most likely somewhere else. Intel GPU compiler stack is very capable when it comes to compiling OpenCL, C for Metal and DPC++. It's not yet very good at compiling ZLUDA. ZLUDA emits code patterns never seen before by the Intel GPU compiler stack and hits some rarely used (or not used before) code paths in the compiler.\ Current status of failing GeekBench tests is tracked [here](https://github.com/vosen/ZLUDA/pull/12) @@ -49,23 +49,27 @@ Overall in this suite of benchmarks faster by approximately 4% on ZLUDA. ## Usage -**Warning**: this is a very incomplete Proof of Concept. It's probably not going to work with your application. ZLUDA currently works only with applications which use CUDA Driver API. Linux builds also work with application which use statically-linked CUDA Runtime API +**Warning**: this is a very incomplete Proof of Concept. It's probably not going to work with your application. ZLUDA currently works only with applications which use CUDA Driver API. Linux builds also work with applications which use statically-linked CUDA Runtime API ### Windows -You should have very recent GPU drivers installed.\ +You should have the most recent GPU drivers installed.\ Copy `nvcuda.dll` to the application directory (the directory where .exe file is) and launch it normally ### Linux -Very recent version of [compute-runtime](https://github.com/intel/compute-runtime) is required. At the time of the writing 20.45.18403 is the recommended version. +A very recent version of [compute-runtime](https://github.com/intel/compute-runtime) is required. At the time of the writing 20.45.18403 is the recommended version. Unpack the archive somewhere and run your application like this: ``` LD_LIBRARY_PATH=<PATH_TO_THE_DIRECTORY_WITH_ZLUDA_PROVIDED_LIBCUDA> <YOUR_APPLICATION> ``` ## Building -You should have relatively recent version of Rust installed, then you just do: +You should have a relatively recent version of Rust installed, then you just do: ``` cargo build ``` -in the main directory of the project
\ No newline at end of file +in the main directory of the project + +## License + +This software is dual-licensed under either the Apache 2.0 license or the MIT license. See [LICENSE-APACHE](LICENSE-APACHE) or [LICENSE-MIT](LICENSE-MIT) for details |