CUTLASS 2.0 Substantially refactored for - Better performance, particularly for native Turing Tensor Cores - Robust and durable templates spanning the design space - Encapsulated functionality embodying modern C++11 programming techniques - Optimized containers and data types for efficient, generic, portable device code Updates to: - Quick start guide - Documentation - Utilities - CUTLASS Profiler Native Turing Tensor Cores - Efficient GEMM kernels targeting Turing Tensor Cores - Mixed-precision floating point, 8-bit integer, 4-bit integer, and binarized operands Coverage of existing CUTLASS functionality: - GEMM kernels targeting CUDA and Tensor Cores in NVIDIA GPUs - Volta Tensor Cores through native mma.sync and through WMMA API - Optimizations such as parallel reductions, threadblock rasterization, and intra-threadblock reductions - Batched GEMM operations - Complex-valued GEMMs Note: this commit and all that follow require a host compiler supporting C++11 or greater.
61 lines
1.1 KiB
CSS
61 lines
1.1 KiB
CSS
.tabs, .tabs2, .tabs3 {
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background-image: url('tab_b.png');
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width: 100%;
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z-index: 101;
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font-size: 13px;
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font-family: 'Lucida Grande',Geneva,Helvetica,Arial,sans-serif;
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}
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.tabs2 {
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font-size: 10px;
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}
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.tabs3 {
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font-size: 9px;
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}
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.tablist {
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margin: 0;
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padding: 0;
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display: table;
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}
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.tablist li {
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float: left;
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display: table-cell;
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background-image: url('tab_b.png');
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line-height: 36px;
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list-style: none;
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}
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.tablist a {
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display: block;
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padding: 0 20px;
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font-weight: bold;
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background-image:url('tab_s.png');
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background-repeat:no-repeat;
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background-position:right;
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color: #3E5035;
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text-shadow: 0px 1px 1px rgba(255, 255, 255, 0.9);
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text-decoration: none;
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outline: none;
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}
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.tabs3 .tablist a {
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padding: 0 10px;
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}
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.tablist a:hover {
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background-image: url('tab_h.png');
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background-repeat:repeat-x;
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color: #fff;
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text-shadow: 0px 1px 1px rgba(0, 0, 0, 1.0);
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text-decoration: none;
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}
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.tablist li.current a {
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background-image: url('tab_a.png');
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background-repeat:repeat-x;
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color: #fff;
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text-shadow: 0px 1px 1px rgba(0, 0, 0, 1.0);
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}
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