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rocBLAS Alternatives
Similar projects and alternatives to rocBLAS
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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AdaptiveCpp
Implementation of SYCL and C++ standard parallelism for CPUs and GPUs from all vendors: The independent, community-driven compiler for C++-based heterogeneous programming models. Lets applications adapt themselves to all the hardware in the system - even at runtime!
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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kokkos-kernels
Kokkos C++ Performance Portability Programming Ecosystem: Math Kernels - Provides BLAS, Sparse BLAS and Graph Kernels
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hipBLASLt
hipBLASLt is a library that provides general matrix-matrix operations with a flexible API and extends functionalities beyond a traditional BLAS library
rocBLAS reviews and mentions
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Nvidia DGX GH200: The First 100 Terabyte GPU Memory System
The same is also true for https://github.com/ROCmSoftwarePlatform/rocBLAS and https://github.com/ROCmSoftwarePlatform/hipBLASLt although the build stack, distribution— leaves a lot to be desired, and otherwise quite unstable.
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Whisper.cpp v1.4.0
Full circle eh. I wonder how well it compares to just trying to use the actual Whisper models on a variety of existing Gpu capable bigger frameworks.
I don't know much practically about how hard it would be to take the Whisper PyTorch (1 or 2?) trained models & to make good use of them elsewhere. I expect Whisper.cpp probably better caters to users, is more readily consumable.
Fwiw, Whisper.cpp uses Nvidia's cuBLAS. There does appear to be an AMD rocm port. https://github.com/ROCmSoftwarePlatform/rocBLAS
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which CPU to choose?
It's not what you asked, but I felt I should point out that rocBLAS is no longer maintained for gfx803 (the architecture of the RX 570) and PyTorch depends on rocBLAS. PyTorch will work at least to some extent, but there are known bugs that may never be fixed. I've been trying to change this, but that's how things are right now.
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Trying to get Pytorch ROCm to work on Ubuntu 20.04 with Fiji cards
The last release that officially supported gfx803 was ROCm 3.5. All testing on that hardware ceased shortly after said release, and the code paths for that architecture have been unmaintained for nearly two years. For a specific example of a problem you may encounter, see: https://github.com/ROCmSoftwarePlatform/rocBLAS/issues/1218
- Compute Ecosystem of AMD GPUs
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PyTorch 1.8 adds AMD ROCm support
Although the code is still there, support for (slightly) older devices are already suffering from lack of maintainence and bugs. For instance there's a bug causing gfx803 devices to produce wrong outputs starting from mid-2020, and I'm pretty sure they're never gonna fix it.
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A note from our sponsor - SaaSHub
www.saashub.com | 25 Apr 2024
Stats
ROCm/rocBLAS is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
The primary programming language of rocBLAS is C++.
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