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src/cmd/internal/sys/arch.go
// for calls. HasLR bool // FixedFrameSize is the smallest possible offset from the // hardware stack pointer to a local variable on the stack. // Architectures that use a link register save its value on // the stack in the function prologue and so always have a // pointer between the hardware stack pointer and the local // variable area. FixedFrameSize int64 }
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Fri May 13 19:51:03 UTC 2022 - 6.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/transforms.h
void AddTFToStablehloPasses(OpPassManager& pm, bool skip_resize, bool smuggle_disallowed_ops); // This function is a common entry point for all graph optimizations that are // not specific to any hardware. It legalizes SHLO->MHLO, does MHLO->MHLO // optimizations by calling `AddMhloOptimizationPasses` internally, and // legalizes MHLO->SHLO void AddStablehloOptimizationPasses(OpPassManager& pm);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 01:08:27 UTC 2024 - 1.9K bytes - Viewed (0) -
testing/precondition-tester/README.md
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Thu Apr 04 07:21:38 UTC 2024 - 1.6K bytes - Viewed (0) -
src/cmd/compile/internal/ssa/lower.go
continue // ok not to lower case OpMakeResult: if b.Controls[0] == v { continue } case OpGetG: if f.Config.hasGReg { // has hardware g register, regalloc takes care of it continue // ok not to lower } } s := "not lowered: " + v.String() + ", " + v.Op.String() + " " + v.Type.SimpleString() for _, a := range v.Args {
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Thu Feb 16 00:16:13 UTC 2023 - 1.7K bytes - Viewed (0) -
doc/next/7-ports.md
The `GOARM64` environment variable defaults to `v8.0`. ### RISC-V {#riscv} <!-- go.dev/issue/61476, CL 541135 -->
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Tue Jun 11 17:18:52 UTC 2024 - 1.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/g3doc/_index.yaml
will include the application of HPC techniques, along with integration of search algorithms like reinforcement learning. MLIR aims to reduce the cost to bring up new hardware, and improve usability for existing TensorFlow users. - code_block: | <pre class = "prettyprint"> // Syntactically similar to LLVM: func @testFunction(%arg0: i32) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Oct 13 16:33:28 UTC 2021 - 2.4K bytes - Viewed (0) -
src/net/mac.go
// Use of this source code is governed by a BSD-style // license that can be found in the LICENSE file. package net const hexDigit = "0123456789abcdef" // A HardwareAddr represents a physical hardware address. type HardwareAddr []byte func (a HardwareAddr) String() string { if len(a) == 0 { return "" } buf := make([]byte, 0, len(a)*3-1) for i, b := range a { if i > 0 {
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon Apr 11 16:34:30 UTC 2022 - 1.9K bytes - Viewed (0) -
platforms/core-execution/execution/src/main/java/org/gradle/internal/execution/steps/Result.java
* in the current build for a number of reasons: * * <ul> * <li>reused work could have happened on a remote machine with different hardware capabilities,</li> * <li>there might have been more or less load on the machine producing the reused work,</li> * <li>the work reused might have been executed incrementally,</li>
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Fri Sep 22 09:46:15 UTC 2023 - 2.5K bytes - Viewed (0) -
docs/distributed/DECOMMISSION.md
# Decommissioning Decommissiong is a mechanism in MinIO to drain older pools (usually with old hardware) and migrate the content from such pools to a newer pools (usually better hardware). Decommissioning spreads the data across all pools - for example, if you decommission `pool1`, all the data from `pool1` spreads across `pool2` and `pool3`. ## Features
Registered: Sun Jun 16 00:44:34 UTC 2024 - Last Modified: Mon Jul 11 14:59:49 UTC 2022 - 8.3K bytes - Viewed (0) -
src/runtime/memclr_amd64.s
MOVOU X15, 240(DI) SUBQ $256, BX ADDQ $256, DI CMPQ BX, $256 JAE loop JMP tail #endif loop_preheader_avx2: VPXOR X0, X0, X0 // For smaller sizes MOVNTDQ may be faster or slower depending on hardware. // For larger sizes it is always faster, even on dual Xeons with 30M cache. // TODO take into account actual LLC size. E. g. glibc uses LLC size/2. CMPQ BX, $0x2000000 JAE loop_preheader_avx2_huge loop_avx2:
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Tue May 10 20:52:34 UTC 2022 - 4.9K bytes - Viewed (0)