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diff --git a/src/vendorcode/amd/agesa/Proc/Mem/Feat/PARTRN/mfParallelTraining.c b/src/vendorcode/amd/agesa/Proc/Mem/Feat/PARTRN/mfParallelTraining.c
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+/* $NoKeywords:$ */
+/**
+ * @file
+ *
+ * mfParallelTraining.c
+ *
+ * This is the parallel training feature
+ *
+ * @xrefitem bom "File Content Label" "Release Content"
+ * @e project: AGESA
+ * @e sub-project: (Mem/Feat/PARTRN)
+ * @e \$Revision: 35136 $ @e \$Date: 2010-07-16 11:29:48 +0800 (Fri, 16 Jul 2010) $
+ *
+ **/
+/*
+ *****************************************************************************
+ *
+ * Copyright (c) 2011, Advanced Micro Devices, Inc.
+ * All rights reserved.
+ *
+ * Redistribution and use in source and binary forms, with or without
+ * modification, are permitted provided that the following conditions are met:
+ * * Redistributions of source code must retain the above copyright
+ * notice, this list of conditions and the following disclaimer.
+ * * Redistributions in binary form must reproduce the above copyright
+ * notice, this list of conditions and the following disclaimer in the
+ * documentation and/or other materials provided with the distribution.
+ * * Neither the name of Advanced Micro Devices, Inc. nor the names of
+ * its contributors may be used to endorse or promote products derived
+ * from this software without specific prior written permission.
+ *
+ * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ * DISCLAIMED. IN NO EVENT SHALL ADVANCED MICRO DEVICES, INC. BE LIABLE FOR ANY
+ * DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+ * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+ *
+ * ***************************************************************************
+ *
+ */
+
+
+
+
+#include "AGESA.h"
+#include "amdlib.h"
+#include "OptionMemory.h"
+#include "mm.h"
+#include "mn.h"
+#include "Ids.h"
+#include "cpuRegisters.h"
+#include "cpuApicUtilities.h"
+#include "mfParallelTraining.h"
+#include "heapManager.h"
+#include "GeneralServices.h"
+#include "Filecode.h"
+CODE_GROUP (G2_PEI)
+RDATA_GROUP (G2_PEI)
+
+#define FILECODE PROC_MEM_FEAT_PARTRN_MFPARALLELTRAINING_FILECODE
+
+/*-----------------------------------------------------------------------------
+ * EXPORTED FUNCTIONS
+ *
+ *-----------------------------------------------------------------------------
+ */
+extern MEM_TECH_CONSTRUCTOR* memTechInstalled[];
+
+/* -----------------------------------------------------------------------------*/
+/**
+ *
+ *
+ * This is the main function to perform parallel training on all nodes.
+ * This is the routine which will run on the remote AP.
+ *
+ * @param[in,out] *EnvPtr - Pointer to the Training Environment Data
+ * @param[in,out] *StdHeader - Pointer to the Standard Header of the AP
+ *
+ * @return TRUE - This feature is enabled.
+ * @return FALSE - This feature is not enabled.
+ */
+BOOLEAN
+MemFParallelTraining (
+ IN OUT REMOTE_TRAINING_ENV *EnvPtr,
+ IN OUT AMD_CONFIG_PARAMS *StdHeader
+ )
+{
+ MEM_PARAMETER_STRUCT ParameterList;
+ MEM_NB_BLOCK NB;
+ MEM_TECH_BLOCK TB;
+ ALLOCATE_HEAP_PARAMS AllocHeapParams;
+ MEM_DATA_STRUCT *MemPtr;
+ DIE_STRUCT *MCTPtr;
+ UINT8 p;
+ UINT8 i;
+ UINT8 Dct;
+ UINT8 Channel;
+ UINT8 *BufferPtr;
+ UINT8 DctCount;
+ UINT8 ChannelCount;
+ UINT8 RowCount;
+ UINT8 ColumnCount;
+ UINT16 SizeOfNewBuffer;
+ AP_DATA_TRANSFER ReturnData;
+
+ //
+ // Initialize Parameters
+ //
+ ReturnData.DataPtr = NULL;
+ ReturnData.DataSizeInDwords = 0;
+ ReturnData.DataTransferFlags = 0;
+
+ ASSERT (EnvPtr != NULL);
+ //
+ // Replace Standard header of a AP
+ //
+ LibAmdMemCopy (StdHeader, &(EnvPtr->StdHeader), sizeof (AMD_CONFIG_PARAMS), &(EnvPtr->StdHeader));
+
+
+ //
+ // Allocate buffer for training data
+ //
+ BufferPtr = (UINT8 *) (&EnvPtr->DieStruct);
+ DctCount = EnvPtr->DieStruct.DctCount;
+ BufferPtr += sizeof (DIE_STRUCT);
+ ChannelCount = ((DCT_STRUCT *) BufferPtr)->ChannelCount;
+ BufferPtr += DctCount * sizeof (DCT_STRUCT);
+ RowCount = ((CH_DEF_STRUCT *) BufferPtr)->RowCount;
+ ColumnCount = ((CH_DEF_STRUCT *) BufferPtr)->ColumnCount;
+
+ SizeOfNewBuffer = sizeof (DIE_STRUCT) +
+ DctCount * (
+ sizeof (DCT_STRUCT) + (
+ ChannelCount * (
+ sizeof (CH_DEF_STRUCT) + sizeof (MEM_PS_BLOCK) + (
+ RowCount * ColumnCount * NUMBER_OF_DELAY_TABLES +
+ (MAX_BYTELANES_PER_CHANNEL * MAX_CS_PER_CHANNEL * NUMBER_OF_FAILURE_MASK_TABLES)
+ )
+ )
+ )
+ );
+ AllocHeapParams.RequestedBufferSize = SizeOfNewBuffer;
+ AllocHeapParams.BufferHandle = GENERATE_MEM_HANDLE (ALLOC_PAR_TRN_HANDLE, 0, 0, 0);
+ AllocHeapParams.Persist = HEAP_LOCAL_CACHE;
+ if (HeapAllocateBuffer (&AllocHeapParams, StdHeader) == AGESA_SUCCESS) {
+ BufferPtr = AllocHeapParams.BufferPtr;
+ LibAmdMemCopy ( BufferPtr,
+ &(EnvPtr->DieStruct),
+ sizeof (DIE_STRUCT) + DctCount * (sizeof (DCT_STRUCT) + ChannelCount * (sizeof (CH_DEF_STRUCT) + sizeof (MEM_PS_BLOCK))),
+ StdHeader
+ );
+
+ //
+ // Fix up pointers
+ //
+ MCTPtr = (DIE_STRUCT *) BufferPtr;
+ BufferPtr += sizeof (DIE_STRUCT);
+ MCTPtr->DctData = (DCT_STRUCT *) BufferPtr;
+ BufferPtr += MCTPtr->DctCount * sizeof (DCT_STRUCT);
+ for (Dct = 0; Dct < MCTPtr->DctCount; Dct++) {
+ MCTPtr->DctData[Dct].ChData = (CH_DEF_STRUCT *) BufferPtr;
+ BufferPtr += MCTPtr->DctData[Dct].ChannelCount * sizeof (CH_DEF_STRUCT);
+ for (Channel = 0; Channel < MCTPtr->DctData[Dct].ChannelCount; Channel++) {
+ MCTPtr->DctData[Dct].ChData[Channel].MCTPtr = MCTPtr;
+ MCTPtr->DctData[Dct].ChData[Channel].DCTPtr = &MCTPtr->DctData[Dct];
+ }
+ }
+ NB.PSBlock = (MEM_PS_BLOCK *) BufferPtr;
+ BufferPtr += DctCount * ChannelCount * sizeof (MEM_PS_BLOCK);
+
+ ReturnData.DataPtr = AllocHeapParams.BufferPtr;
+ ReturnData.DataSizeInDwords = (SizeOfNewBuffer + 3) / 4;
+ ReturnData.DataTransferFlags = 0;
+
+ //
+ // Allocate Memory for the MEM_DATA_STRUCT we will use
+ //
+ AllocHeapParams.RequestedBufferSize = sizeof (MEM_DATA_STRUCT);
+ AllocHeapParams.BufferHandle = AMD_MEM_DATA_HANDLE;
+ AllocHeapParams.Persist = HEAP_LOCAL_CACHE;
+ if (HeapAllocateBuffer (&AllocHeapParams, StdHeader) == AGESA_SUCCESS) {
+ MemPtr = (MEM_DATA_STRUCT *)AllocHeapParams.BufferPtr;
+
+ LibAmdMemCopy (&(MemPtr->StdHeader), &(EnvPtr->StdHeader), sizeof (AMD_CONFIG_PARAMS), StdHeader);
+
+ //
+ // Copy Parameters from environment
+ //
+ ParameterList.HoleBase = EnvPtr->HoleBase;
+ ParameterList.BottomIo = EnvPtr->BottomIo;
+ ParameterList.UmaSize = EnvPtr->UmaSize;
+ ParameterList.SysLimit = EnvPtr->SysLimit;
+ ParameterList.TableBasedAlterations = EnvPtr->TableBasedAlterations;
+ ParameterList.PlatformMemoryConfiguration = EnvPtr->PlatformMemoryConfiguration;
+ MemPtr->ParameterListPtr = &ParameterList;
+
+ for (p = 0; p < MAX_PLATFORM_TYPES; p++) {
+ MemPtr->GetPlatformCfg[p] = EnvPtr->GetPlatformCfg[p];
+ }
+
+ MemPtr->ErrorHandling = EnvPtr->ErrorHandling;
+ //
+ // Create Local NBBlock and Tech Block
+ //
+ EnvPtr->NBBlockCtor (&NB, MCTPtr, EnvPtr->FeatPtr);
+ NB.RefPtr = &ParameterList;
+ NB.MemPtr = MemPtr;
+ i = 0;
+ while (memTechInstalled[i] != NULL) {
+ if (memTechInstalled[i] (&TB, &NB)) {
+ break;
+ }
+ i++;
+ }
+ NB.TechPtr = &TB;
+ NB.TechBlockSwitch (&NB);
+
+ //
+ // Setup CPU Mem Type MSRs on the AP
+ //
+ NB.CpuMemTyping (&NB);
+
+ IDS_HDT_CONSOLE (MEM_STATUS, "Node %d\n", NB.Node);
+ //
+ // Call Technology Specific Training routine
+ //
+ NB.TrainingFlow (&NB);
+ //
+ // Copy training data to ReturnData buffer
+ //
+ LibAmdMemCopy ( BufferPtr,
+ MCTPtr->DctData[0].ChData[0].RcvEnDlys,
+ ((DctCount * ChannelCount) * (
+ (RowCount * ColumnCount * NUMBER_OF_DELAY_TABLES) +
+ (MAX_BYTELANES_PER_CHANNEL * MAX_CS_PER_CHANNEL * NUMBER_OF_FAILURE_MASK_TABLES)
+ )
+ ),
+ StdHeader);
+
+ HeapDeallocateBuffer (AMD_MEM_DATA_HANDLE, StdHeader);
+ //
+ // Restore pointers
+ //
+ for (Dct = 0; Dct < MCTPtr->DctCount; Dct++) {
+ for (Channel = 0; Channel < MCTPtr->DctData[Dct].ChannelCount; Channel++) {
+ MCTPtr->DctData[Dct].ChData[Channel].MCTPtr = &EnvPtr->DieStruct;
+ MCTPtr->DctData[Dct].ChData[Channel].DCTPtr = &EnvPtr->DieStruct.DctData[Dct];
+
+ MCTPtr->DctData[Dct].ChData[Channel].RcvEnDlys = EnvPtr->DieStruct.DctData[Dct].ChData[Channel].RcvEnDlys;
+ MCTPtr->DctData[Dct].ChData[Channel].WrDqsDlys = EnvPtr->DieStruct.DctData[Dct].ChData[Channel].WrDqsDlys;
+ MCTPtr->DctData[Dct].ChData[Channel].RdDqsDlys = EnvPtr->DieStruct.DctData[Dct].ChData[Channel].RdDqsDlys;
+ MCTPtr->DctData[Dct].ChData[Channel].WrDatDlys = EnvPtr->DieStruct.DctData[Dct].ChData[Channel].WrDatDlys;
+ MCTPtr->DctData[Dct].ChData[Channel].RdDqsMinDlys = EnvPtr->DieStruct.DctData[Dct].ChData[Channel].RdDqsMinDlys;
+ MCTPtr->DctData[Dct].ChData[Channel].RdDqsMaxDlys = EnvPtr->DieStruct.DctData[Dct].ChData[Channel].RdDqsMaxDlys;
+ MCTPtr->DctData[Dct].ChData[Channel].WrDatMinDlys = EnvPtr->DieStruct.DctData[Dct].ChData[Channel].WrDatMinDlys;
+ MCTPtr->DctData[Dct].ChData[Channel].WrDatMaxDlys = EnvPtr->DieStruct.DctData[Dct].ChData[Channel].WrDatMaxDlys;
+ MCTPtr->DctData[Dct].ChData[Channel].FailingBitMask = EnvPtr->DieStruct.DctData[Dct].ChData[Channel].FailingBitMask;
+ }
+ MCTPtr->DctData[Dct].ChData = EnvPtr->DieStruct.DctData[Dct].ChData;
+ }
+ MCTPtr->DctData = EnvPtr->DieStruct.DctData;
+ }
+
+ //
+ // Signal to BSP that training is complete and Send Results
+ //
+ ASSERT (ReturnData.DataPtr != NULL);
+ ApUtilTransmitBuffer (EnvPtr->BspSocket, EnvPtr->BspCore, &ReturnData, StdHeader);
+
+ //
+ // Clean up and exit.
+ //
+ HeapDeallocateBuffer (GENERATE_MEM_HANDLE (ALLOC_PAR_TRN_HANDLE, 0, 0, 0), StdHeader);
+ } else {
+ MCTPtr = &EnvPtr->DieStruct;
+ PutEventLog (AGESA_FATAL, MEM_ERROR_HEAP_ALLOCATE_FOR_TRAINING_DATA, MCTPtr->NodeId, 0, 0, 0, StdHeader);
+ SetMemError (AGESA_FATAL, MCTPtr);
+ ASSERT(FALSE); // Could not allocate heap for buffer for parallel training data
+ }
+ return TRUE;
+}