group files

- move source code to `src`
- categorize files and move to group folder
- change upper case class files to lower case
- change C++ header to `*.hpp`

1 files changed, 113 insertions, 0 deletions

diff --git a/xmrstak/backend/nvidia/autoAdjust.hpp b/xmrstak/backend/nvidia/autoAdjust.hpp
new file mode 100644
index 0000000..84c6dfc
--- /dev/null
+++ b/xmrstak/backend/nvidia/autoAdjust.hpp
@@ -0,0 +1,113 @@
+
+#pragma once
+
+#include "autoAdjust.hpp"
+
+#include "nvcc_code/cryptonight.h"
+#include "jconf.h"
+#include "../../console.h"
+#include "../../ConfigEditor.hpp"
+#include "../../Params.hpp"
+
+#include <vector>
+#include <cstdio>
+#include <sstream>
+#include <string>
+
+
+namespace xmrstak
+{
+namespace nvidia
+{
+
+class autoAdjust
+{    
+public:
+
+    autoAdjust()
+    {
+
+    }
+
+    /** print the adjusted values if needed
+     *
+     * Routine exit the application and print the adjusted values if needed else
+     * nothing is happened.
+     */
+    bool printConfig()
+    {
+		int deviceCount = 0;
+        if(cuda_get_devicecount(&deviceCount) == 0)
+            std::exit(0);
+        // evaluate config parameter for if auto adjustment is needed
+                // evaluate config parameter for if auto adjustment is needed
+        for(int i = 0; i < deviceCount; i++)
+        {
+       
+            nvid_ctx ctx;
+
+            ctx.device_id = i;
+            // -1 trigger auto adjustment
+            ctx.device_blocks = -1;
+            ctx.device_threads = -1;
+
+        // set all evice option those marked as auto (-1) to a valid value
+#ifndef _WIN32
+            ctx.device_bfactor = 0;
+            ctx.device_bsleep = 0;
+#else
+            // windows pass, try to avoid that windows kills the miner if the gpu is blocked for 2 seconds
+            ctx.device_bfactor = 6;
+            ctx.device_bsleep = 25;
+#endif
+            if( cuda_get_deviceinfo(&ctx) != 1 )
+            {
+                printer::inst()->print_msg(L0, "Setup failed for GPU %d. Exitting.\n", i);
+                std::exit(0);
+            }
+            nvidCtxVec.push_back(ctx);
+
+        }
+
+        generateThreadConfig();
+		return true;
+
+    }
+
+private:
+    
+    void generateThreadConfig()
+    {
+		// load the template of the backend config into a char variable
+		const char *tpl =
+			#include "./config.tpl"
+		;
+
+		ConfigEditor configTpl{};
+		configTpl.set( std::string(tpl) );
+
+		constexpr size_t byte2mib = 1024u * 1024u;
+		std::string conf;
+        int i = 0;
+        for(auto& ctx : nvidCtxVec)
+        {
+			conf += std::string("  // gpu: ") + ctx.name + " architecture: " + std::to_string(ctx.device_arch[0] * 10 + ctx.device_arch[1]) + "\n";
+			conf += std::string("  //      memory: ") + std::to_string(ctx.free_device_memory / byte2mib) + "/"  + std::to_string(ctx.total_device_memory / byte2mib) + " MiB\n";
+            conf += std::string("  { \"index\" : ") + std::to_string(ctx.device_id) + ",\n" +
+                "    \"threads\" : " + std::to_string(ctx.device_threads) + ", \"blocks\" : " + std::to_string(ctx.device_blocks) + ",\n" +
+                "    \"bfactor\" : " + std::to_string(ctx.device_bfactor) + ", \"bsleep\" :  " + std::to_string(ctx.device_bsleep) + ",\n" +
+                "    \"affine_to_cpu\" : false,\n" +
+                "  },\n";
+            ++i;
+        }
+
+		configTpl.replace("GPUCONFIG",conf);
+		configTpl.write(Params::inst().configFileNVIDIA);
+		printer::inst()->print_msg(L0, "NVIDIA: GPU configuration stored in file '%s'", Params::inst().configFileNVIDIA.c_str());
+    }
+
+    std::vector<nvid_ctx> nvidCtxVec;
+};
+
+} // namespace nvidia
+} // namepsace xmrstak