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boinc/lib/coproc.h

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// This file is part of BOINC.
// http://boinc.berkeley.edu
// Copyright (C) 2008 University of California
//
// BOINC is free software; you can redistribute it and/or modify it
// under the terms of the GNU Lesser General Public License
// as published by the Free Software Foundation,
// either version 3 of the License, or (at your option) any later version.
//
// BOINC is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
// See the GNU Lesser General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public License
// along with BOINC. If not, see <http://www.gnu.org/licenses/>.
// Structures representing coprocessors (e.g. GPUs);
// used in both client and server.
//
// Notes:
//
// 1) The use of "CUDA" is misleading; it really means "NVIDIA GPU".
// 2) The design treats each resource type as a pool of identical devices;
// for example, there is a single "CUDA long-term debt" per project,
// and a scheduler request contains a request (#instances, instance-seconds)
// for CUDA jobs.
// In reality, the instances of a resource type can have different properties:
// In the case of CUDA, "compute capability", driver version, RAM, speed, etc.
// How to resolve this discrepancy?
//
// Prior to 21 Apr 09 we identified the fastest instance
// and pretended that the others were identical to it.
// This approach has a serious flaw:
// suppose that the fastest instance has characteristics
// (version, RAM etc.) that satisfy the project's requirements,
// but other instances to not.
// Then BOINC executes jobs on GPUs that can't handle them,
// the jobs fail, the host is punished, etc.
//
// We could treat each GPU has a separate resource,
// with its own set of debts, backoffs, etc.
// However, this would imply tying jobs to instances,
// which is undesirable from a scheduling viewpoint.
// It would also be a big code change in both client and server.
//
// Instead, (as of 21 Apr 09) our approach is to identify a
// "most capable" instance, which in the case of CUDA is based on
// a) compute capability
// b) driver version
// c) RAM size
// d) est. FLOPS
// (in decreasing priority).
// We ignore and don't use any instances that are less capable
// on any of these axes.
//
// This design avoids running coprocessor apps on instances
// that are incapable of handling them, and it involves no server changes.
// Its drawback is that, on systems with multiple and differing GPUs,
// it may not use some GPUs that actually could be used.
#ifndef _COPROC_
#define _COPROC_
#include <vector>
#include <string>
#include <cstring>
#ifdef _USING_FCGI_
#include "boinc_fcgi.h"
#endif
#include "miofile.h"
#include "cal_boinc.h"
#define MAX_COPROC_INSTANCES 64
// represents a requirement for a coproc.
// This is a parsed version of the <coproc> elements in an <app_version>
// (used in client only)
//
struct COPROC_REQ {
char type[256]; // must be unique
double count;
int parse(MIOFILE&);
};
// represents a coproc on a particular computer.
// Abstract class;
// objects will always be a derived class (COPROC_CUDA, COPROC_ATI)
// Used in both client and server.
//
struct COPROC {
char type[256]; // must be unique
int count; // how many are present
double used; // how many are in use (used by client)
// the following are used in both client and server for work-fetch info
//
double req_secs;
// how many instance-seconds of work requested
double req_instances;
// client is requesting enough jobs to use this many instances
double estimated_delay;
// resource will be saturated for this long
// temps used in client (enforce_schedule())
// to keep track of what fraction of each instance is in use
// during instance assignment
//
double usage[MAX_COPROC_INSTANCES];
double pending_usage[MAX_COPROC_INSTANCES];
// the device number of each instance
// These are not sequential if we omit instances (see above)
//
int device_nums[MAX_COPROC_INSTANCES];
int device_num; // temp used in scan process
bool running_graphics_app[MAX_COPROC_INSTANCES];
// is this GPU running a graphics app (NVIDIA only)
double available_ram[MAX_COPROC_INSTANCES];
bool available_ram_unknown[MAX_COPROC_INSTANCES];
// couldn't get available RAM; don't start new apps on this instance
double available_ram_fake[MAX_COPROC_INSTANCES];
double last_print_time;
#ifndef _USING_FCGI_
virtual void write_xml(MIOFILE&);
#endif
inline void clear() {
// can't just memcpy() - trashes vtable
type[0] = 0;
count = 0;
used = 0;
req_secs = 0;
req_instances = 0;
estimated_delay = 0;
for (int i=0; i<MAX_COPROC_INSTANCES; i++) {
device_nums[i] = 0;
running_graphics_app[i] = true;
available_ram[i] = 0;
available_ram_fake[i] = 0;
available_ram_unknown[i] = true;
}
}
inline void clear_usage() {
for (int i=0; i<count; i++) {
usage[i] = 0;
pending_usage[i] = 0;
}
}
COPROC(const char* t){
clear();
strcpy(type, t);
}
COPROC() {
clear();
}
virtual ~COPROC(){}
int parse(MIOFILE&);
void print_available_ram();
};
// based on cudaDeviceProp from /usr/local/cuda/include/driver_types.h
// doesn't have to match exactly since we get the attributes one at a time.
//
struct CUDA_DEVICE_PROP {
char name[256];
unsigned int totalGlobalMem;
// not used on the server; dtotalGlobalMem is used instead
// (since some boards have >= 4GB)
int sharedMemPerBlock;
int regsPerBlock;
int warpSize;
int memPitch;
int maxThreadsPerBlock;
int maxThreadsDim[3];
int maxGridSize[3];
int clockRate;
int totalConstMem;
int major; // compute capability
int minor;
int textureAlignment;
int deviceOverlap;
int multiProcessorCount;
double dtotalGlobalMem; // not defined in client
};
struct COPROC_CUDA : public COPROC {
int cuda_version; // CUDA runtime version
int display_driver_version;
CUDA_DEVICE_PROP prop;
#ifndef _USING_FCGI_
virtual void write_xml(MIOFILE&);
#endif
COPROC_CUDA(): COPROC("CUDA"){}
virtual ~COPROC_CUDA(){}
void get(
bool use_all,
std::vector<std::string>&, std::vector<std::string>&,
std::vector<int>& ignore_devs
);
void description(char*);
void clear();
int parse(MIOFILE&);
// Estimate of peak FLOPS.
// FLOPS for a given app may be much less;
// e.g. for SETI@home it's about 0.18 of the peak
//
inline double peak_flops() {
// clock rate is scaled down by 1000;
// each processor has 8 or 32 cores;
// each core can do 2 ops per clock
//
int cores_per_proc = (prop.major>=2)?32:8;
double x = (1000.*prop.clockRate) * prop.multiProcessorCount * cores_per_proc * 2.;
return x?x:5e10;
}
void get_available_ram();
bool check_running_graphics_app();
void fake(int driver_version, double ram, int count);
};
enum CUdevice_attribute_enum {
CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK = 1,
CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X = 2,
CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Y = 3,
CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Z = 4,
CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X = 5,
CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Y = 6,
CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Z = 7,
CU_DEVICE_ATTRIBUTE_SHARED_MEMORY_PER_BLOCK = 8,
CU_DEVICE_ATTRIBUTE_TOTAL_CONSTANT_MEMORY = 9,
CU_DEVICE_ATTRIBUTE_WARP_SIZE = 10,
CU_DEVICE_ATTRIBUTE_MAX_PITCH = 11,
CU_DEVICE_ATTRIBUTE_REGISTERS_PER_BLOCK = 12,
CU_DEVICE_ATTRIBUTE_CLOCK_RATE = 13,
CU_DEVICE_ATTRIBUTE_TEXTURE_ALIGNMENT = 14,
CU_DEVICE_ATTRIBUTE_GPU_OVERLAP = 15,
CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT = 16,
CU_DEVICE_ATTRIBUTE_KERNEL_EXEC_TIMEOUT = 17,
CU_DEVICE_ATTRIBUTE_INTEGRATED = 18,
CU_DEVICE_ATTRIBUTE_CAN_MAP_HOST_MEMORY = 19,
CU_DEVICE_ATTRIBUTE_COMPUTE_MODE = 20
};
struct COPROC_ATI : public COPROC {
char name[256];
char version[50];
int version_num;
bool atirt_detected;
bool amdrt_detected;
CALdeviceattribs attribs;
CALdeviceinfo info;
#ifndef _USING_FCGI_
virtual void write_xml(MIOFILE&);
#endif
COPROC_ATI(): COPROC("ATI"){}
virtual ~COPROC_ATI(){}
void get(
bool use_all,
std::vector<std::string>&, std::vector<std::string>&,
std::vector<int>& ignore_devs
);
void description(char*);
void clear();
int parse(MIOFILE&);
inline double peak_flops() {
double x = attribs.numberOfSIMD * attribs.wavefrontSize * 2.5 * attribs.engineClock * 1.e6;
// clock is in MHz
return x?x:5e10;
}
void get_available_ram();
void fake(double, int);
};
struct COPROCS {
COPROC_CUDA cuda;
COPROC_ATI ati;
COPROCS(){}
~COPROCS(){} // don't delete coprocs; else crash in APP_INIT_DATA logic
void write_xml(MIOFILE& out);
void get(
bool use_all, std::vector<std::string> &descs,
std::vector<std::string> &warnings,
std::vector<int>& ignore_cuda_dev,
std::vector<int>& ignore_ati_dev
);
int parse(MIOFILE&);
void summary_string(char*, int);
bool fully_used() {
if (cuda.used < cuda.count) return false;
if (ati.used < ati.count) return false;
return true;
}
// Copy a coproc set, possibly setting usage to zero.
// used in round-robin simulator and CPU scheduler,
// to avoid messing w/ master copy
//
void clone(COPROCS& c, bool copy_used) {
cuda = c.cuda;
ati = c.ati;
if (!copy_used) {
cuda.used = 0;
ati.used = 0;
}
}
inline void clear() {
cuda.count = 0;
ati.count = 0;
}
inline void clear_usage() {
cuda.clear_usage();
ati.clear_usage();
}
inline bool none() {
return (cuda.count==0) && (ati.count==0);
}
inline int ndevs() {
return cuda.count + ati.count;
}
};
#endif
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